• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.941-947
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• 2002

Two methods of constructing T-S fuzzy model which is equivalent to a given nonlinear system are presented. The first method is to obtain an equivalent T-S fuzzy model by using the sum of linearly independent scalar functions with constant real matrix coefficients. The sum of products of linearly independent scalar functions is used in the second method. The former method is to formulate the procedures of T-S fuzzy modeling dealt in many examples of previous publications; the latter is a new method. By comparing the number of linearly independent functions used in the two methods, we can easily find out which method makes fewer rules than the other. The nonlinear dynamics of an inverted Pendulum on a cart is used as an equivalent T-5 fuzzy modeling example.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.916-921
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• 2002

We presents a new method of constructing an equivalent T-S fuzzy model by using the sum of products of linearly independent scalar functions from nonlinear dynamics. This method exactly expresses nonlinear systems and automatically determines the number of rules. We design a stabilizing controller f3r ul inverted pendulum system by using the concep of parallel distributed compensation (PDC) and linear matrix inequalities (LMIs) based on the proposed T-S fuzzy modeling method. We show effectiveness of a systematically designed fuzzy controller based on the proposed T-S fuzzy modeling method through the simulation and experiment of an inverted pendulum system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2264-2269
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• 2003

This paper presents an improved method that constructs an equivalent T-S fuzzy model for nonlinear systems expressed by nonlinear differential equations including terms of power series. The method in this paper has fewer numbers of the rules than the previous methods as well as exactly expresses nonlinear systems. Moreover, this method can get wider feasible area satisfying the stability conditions than the previous methods. We show the improvement of modeling by comparing the proposed method with two previous methods through an inverted pendulum on a cart.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.893-895
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• 2005

We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system. intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3105-3107
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• 2005

We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system. Intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2453-2455
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• 2005

We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system Intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows re matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1811-1813
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• 2005

We represent an efficient intelligent digital redesign method for a Takagi-Sugeno(T-S) fuzzy system. Intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality(LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.420-428
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• 2012

In this paper, a novel intelligent digital redesign (IDR) technique is proposed for the nonlinear interconnected systems which can be represented by a Takagi-Sugeno (T-S) fuzzy model. The IDR technique is to convert a pre-designed analog controller into an equivalent digital one. To develop this method, the discretized models of the analog and digital closed-loop system with the decentralized controller are presented, respectively. Using these discretized models, the digital decentralized control gain is obtained to minimize the norm between the state variables of the analog and digital closed-loop systems and stabilize the digital closed-loop system. Its sufficient conditions are derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to verify the effectiveness of the proposed technique.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).