• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.52-57
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• 2006

In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

• 한국정밀공학회지
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• 제13권6호
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• pp.102-113
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• 1996

An experimental and theoretical study on a pneumatic servo system has been conducted using on-off valves and a pneumatic cylinder. A V/I converter has been designed for rapid rising and falling of the solenoid current, which significantly improves the positioning accuracy and settling time of the servo system by shortening the valve opening time. Pulse width modulation was modified to operate on-off valves effectively. A state feedback controller which feeds back position, velocity and acceleration is used to control the system. The influence of controller gains on the system performance is studied to develop a scheme that automatically adjusts the gains using fuzzy logic theory. It is shown experimentally that the proposed fuzzy logic tuner works satisfactorily. A new method for measurements of valve effective areas is proposed, and a partially polytropic model is applied to simulation of the pneumatic system. Simulated results show good agreement with experimental data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.83.4-83
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• 2002

$\bullet$ We present a state-feedback RHC for discrete-time TS fuzzy systems with input constriants. $\bullet$ The controller employ the current and one-step past information on the fuzzy weighting functions. $\bullet$ It is obtained from the finite horizon optimization problem with the invariant ellipsoid constraint $\bullet$ Under parameterized LMI conditions on the terminal weighting matrix $\bullet$ The closed-loop system stability is guaranteed. $\bullet$ The parameterized linear matrix inequalities are relaxed to a finite number of solvable LMIs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2815-2817
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• 2005

This paper presents an experiment study on the control of a rotary-type inverted pendulum based on the Takagi-Sugeno (T-S) fuzzy model approach. A sufficient condition for stability of the T-S fuzzy control system is given via linear matrix inequalities (LMIs). State-feedback controllers for sub-systems are designed from the sufficient condition via change of variables which is one of the popular LMI techniques. Experimental results on a rotary-type inverted pendulum control show the feasibility of the T-S fuzzy model-based control method.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.179-181
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• 2004

This paper is proposed an adaptive fuzzy-neural network(A-FNN) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using A closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.459-464
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• 1998

In this paper, we propose a stable fuzzy logic controller architecture for inverted pendulum,. In the design procedure, we represent the fuzzy system as a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller by considering each local state feedback controller and a supervisory controller, Unlike usual parallel distributed controller, one can design a global stable fuzzy controller without finding a common Lyapunov function by the proposed method. A simulation is performed to control the inverted pendulum to show the effectiveness and feasibility of the proposed fuzzy controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.166-172
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• 2003

The dynamics of the DDWMR depends on the velocity difference of the two driving wheels. And which is known as a type of non-holonomic equation. By this reason, the treatment of DDWMR had become difficult and conservative. In this paper, the differential-driving wheeled mobile robot is considered. The Takaki-Surgeno fuzzy model and a control method for DDWMR is presented. The suggested controller has three control elements. The first element is fuzzy state feedback designed for eliminating the dependence of time-varying parameter. The second element is weighting controller which is designed for good frequency response. The third controller is PI-controller which is designed for good command following and robustness with un-modeled dynamics. In order for achieving the performance objective, the design of controller is based on the loop-shaping algorithm.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권2호
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• pp.68-73
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex nonlinear systems. Firstly, the nonlinear system is represented by Takagi-Sugeno(TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller is composed of two processes. One is to determine the static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative methods for the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method, the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. A numerical simulation example is given to show the effectiveness and feasibiltiy of the proposed fuzzy controller design method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1081-1082
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• 2008

This paper presents adaptive fuzzy control based on observer for nonlinear HVAC system whose states are not available. Fuzzy systems are employed to approximate the unknown nonlinear functions of the HVAC system and the state observer is designed for estimating the states of the HVAC system. An adaptive fuzzy controller is firstly constructed without the controller singularity problem. The obtained control system shows robustness and effectiveness compared with classical feedback controller. Simulation results are provided to illustrate the control performance.