• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.405-414
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• 2016

This paper presents an internal oil leakage detection problem for a hydraulic single-rod cylinder. We derive the dynamics of the hydraulic cylinder as a state space model, and then design a T—S fuzzy model-based fault detection observer. We adopt an H_∞ observer design scheme so that the observer is robust against disturbance and relatively sensitive to the leakage fault. Sufficient design conditions are derived in the form of linear matrix inequalities. A numerical example is provided to verify the proposed techniques.

• Journal of Environmental Science International
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• v.15 no.2
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.151-157
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• 2008

A non-fragile guaranteed cost control (GCC) problem is presented for a class of discrete time-delay nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The systems are assumed to have norm-bounded time-varying uncertainties in the matrices of state, delayed state and control gains. Sufficient conditions are first obtained which guarantee that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound. Then the design method of the non-fragile guaranteed cost controller is formulated in terms of the linear matrix inequality (LMI) approach. A numerical example is given to illustrate the effectiveness of the proposed design method.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.457-465
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• 2004

Ramik[7] introduced a fuzzy goal programming (FGP)problem that generalizes a standard goal programming (GP) problem with fuzzy alternatives, fuzzy objective functions and fuzzy deviation functions for measuring the deviation between attained and desired goals being fuzzy. However, it is known that this FGP tends to produce an approximate solution since it uses an approximate fuzzy multiplication operation to solve the resultant fuzzy model. In this paper, we show that this FGP sometimes leads to the wrong decision. We also propose a procedure that gets the exact solution to overcome these problems. The method is based on $T_M$ (min norm)-based fuzzy operations using $\alpha-cut$ representations. We consider the same example as used in Ramik and investigate how our procedures are compared to Ramik's.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.549-554
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• 2012

In this paper, we consider the optimal fuzzy filter of nonlinear discrete-time with estimation error variance constraint. First, the Takagi and Sugeno(T-S) fuzzy model is employed to approximate the nonlinear system. Next, the error state is mean square bounded, and the steady state variance of the estimation error of each state is not more than the individual predefined value. It is shown that, the addressed problem can be carried out by solving linear matrix inequality(LMI) and some algebraic quadratic matrix inequalities. Finally, some examples are provided to illustrate the design procedure and expected performance through simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.185-190
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• 2005

A systematic output tracking control design technique for robust control of Takagi-Sugeno (T-S) fuzzy systems with norm bounded uncertainties is developed. The uncertain T-S fuzzy system is first represented as a set of uncertain local linear systems. The tracking problem is then converted into the stabilization problem for a set of uncertain local linear systems thereby leading to a more feasible controller design procedure. A sufficient condition for robust asymptotic output tracking is derived in terms of a set of linear matrix inequalities. A stability condition on the traversing time instances is also established. The output tracking control simulation for a flexible-joint robot-arm model is demonstrated, to convincingly show the effectiveness of the proposed system modeling and controller design.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.123-137
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• 2024

In this paper, Power fuzzy graphs is newly introduced by allotting fuzzy values on power graphs in such a way that the newly added edges, has the edge membership values between a closed interval which depends on vertex membership values and the length of the added edges. Power fuzzy subgraphs and total power fuzzy graphs are newly defined with properties and some special cases. It is observed that every power fuzzy graph is a fuzzy graph but the converse need not be true. Edges that are incident to vertices with the least vertex membership values are retained in the least power fuzzy subgraph. Further, the application of these concepts in real life time has been presented and discussed using power fuzzy graph model.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2354-2356
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• 1998

We present a fuzzy model for a robot manipulator and use the model to decide the PD gains of a stiffness controller. Force control applications are extremely difficult to accomplish with such a stiffness robot because robot itself, unknown environment. So we identify a fuzzy model by using Hough transform. We present a method of design of the PD gains of the stiffness controller. We aim at controlling the end-effecor force in the face of uncertainty on the surface stillness. simulation results verify the effectiveness of the proposed strategy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.353-353
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• 2000

To control a light weight flexible manipulator, a composite fuzzy controller is proposed. The controller is designed based on two time scaled models. A singular perturbation technique is applied for deriving the models. The proposed controller, however, does not use the complex equilibrium manifold equations, which are usually needed in the controller based on the two time scaled models. The controller for a slow sub-model and a fast sub-model are T-S type fuzzy controllers, which use 3 linguistic variables for each sub-model. A step trajectory is used in simulations as a reference trajectory of joint motions. The results of simulations with the proposed controller show excellent damping of flexible motions compared to a controller with derivative control of flexible motions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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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.