• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.429-432
• /
• 1998

This paper is to design stable fuzzy controller so as to control chaotic nonlinear systems effectively via fuzzy control system and Parallel Distributed Compensation (PDC) design. To design fuzzy control system, nonlinear systems are represented by Takagi-sugeno(TS) fuzzy models. The PDC is employed to design fuzzy controllers from the TS fuzzy models. The stability analysis and control design problems is to find a common Lyapunov function for a set of linear matrix inequalitys(LMIs). The designed fuzzy controller is applied to Rossler system. The simulation results show the effectiveness of our controller.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.1
• /
• pp.46-51
• /
• 2004

his paper presents a novel design technique for the TS fuzzy classifier via linear matrix inequalities(LMI). To design the TS fuzzy classifier built by the TS fuzzy model, the consequent parameters are determined to maximize the classifier's performance. Differ from the conventional fuzzy classifier design techniques, convex optimization technique is used to resolve the determination problem. Consequent parameter identification problems are first reformulated to the convex optimization problem. The convex optimization problem is then efficiently solved by converting linear matrix inequality problems. The TS fuzzy classifier has the optimal consequent parameter via the proposed design procedure in sense of the minimum classification error. Simulations are given to evaluate the proposed fuzzy classifier; Iris data classification and Wisconsin Breast Cancer Database data classification. Finally, simulation results show the utility of the integrated linear matrix inequalities approach to design of the TS fuzzy classifier.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2005-2007
• /
• 2001

A controller design problem for a discrete-time Takagi-Sugeno (TS) fuzzy systems is discussed. The switching-type controller is employed in this study. A switching-type fuzzy-model-based controller is constructed based on the spirit of "devide and conquer". The design condition of this controller is formulated in terms of linear matrix inequalities (LMIs), which guarantees the global stability of the controlled TS fuzzy systems. An example is included for ensuring the effecienct of the proposed control method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.3
• /
• pp.208-214
• /
• 2001

본 논문은 시변 입력 지연을 포함한 Takagi-Sugeno (TS) 퍼지 시스템으로 표현 가능한 비선형 시스템을 위한 체계적인 제어기의 설계 기법을 제안한다. 입력 지연은 화학 공정 시스템, 인터넷 기반 가상 실험실, 자율 이동 로봇의 원격 제어등, 실제의 산업 현장에서 매우 빈번히 발생하는 현상이며 제어 시스템의 성능을 감소시키며, 안정성을 저해하는 요소로 알려져 있다. 따라서 본 논문에서 다루고자 하는 문제는 매우 실제적인 문제이며 반드시 해결하여야 할 문제이다. 본 논문은 Lyapunov-Razumikhin 안정 이론에 기반하여 TS 퍼지 모델 기반 제어기의 설계 조건을 제시한다. 최종적인 제어기의 설계 조건은 선형 행렬 부등식의 형태로 주어진다. TS 퍼지모델 기반 제어기가 안정화시킬 수 있는 입력지연의 상한 값을 최대화하기 위하여 이중 최적화 기법을 도입한다. 제안된 제어기 설계 기법의 우수성과 타당성을 입증하기 위하여 모의 실험을 수행하였다. 컴퓨터 시뮬레이션 결과, 본 논문에서 제안한 타당성을 입증할 수 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.2
• /
• pp.139-145
• /
• 2002

In this paper, we proposed an intelligent digital redesign method for a class of fuzzy-model-based controllers, effective fur stabilization of continuous-time nonlinear systems. The TS fuzzy model is used to expend the results of the digital redesign technique to nonlinear systems. The proposed method utilized the recently developed LMI technique to obtain a digitally redesigned fuzzy-model-based controller. The intelligent digital redesign problem is converted to equivalent problem, and the LMI method is used to find the digitally redesigned fuzzy-model-based controller. The stabilization conditions of TS fuzzy model are derived for stabilization in the sense of Laypunov stability. In order to demonstrates the effectiveness and feasibility of the proposed controller design methodology, we applied this method to the single link flexible-joint robot arm.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.187-193
• /
• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.9
• /
• pp.793-800
• /
• 2001

This paper deals with a new design methodology for a switching-type fuzzy-model-based controller in continuous and discrete-time system. Takagi-Sugeno (TS) fuzzy model is employed to design the switching-type fuzzy-model-based controller. A switching-type fuzzy-model-based controller is constructed based on the spirit of “divide and conquer”. The global system which has several rules in divided into several subsystems and then, a solution is found at each subsystem. The global solution is determined by a conjunction of the solutions of each subsystem. The design conditions are formulated in terns of linear matrix inequalities (LMIs), which guarantee the stabilization of a given TS fuzzy system. Simulation examples are included for ensuring the proposed control method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.153-156
• /
• 2001

This paper discusses a stochastic stabilization of Takagi-Sugeno (75) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time 75 fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized 75 fuzzy system is represented by a discrete-time 75 fuzzy system with jumping parameters. The stochastic stabilizibility of the jump 75 fuzzy system is derived and formulated in terms of linear matrix inequalities (LMls).

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.5
• /
• pp.395-399
• /
• 2001

This paper describes modular fuzzy inference systems(MFIS) with adaptive capability to extract fuzzy inference modules from observation data through the learning process. The proposed MFIS is based on the structural similarity to Tagaki-Sugeno fuzzy models and a modular neural architecture. The learning of MFIS is done by assigning new fuzzy inference modules and by updating the parameters of existing modules. The fuzzy inference modules consist of local model network and fuzzy gating network. The parameters of the MFIS are updated by the standard LMS algorithm. The performance of the MFIS is illustrated with adaptive control of a nonlinear dynamic system.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2630-2632
• /
• 2000

In this paper, a control technique of Takagi-Sugeno (TS) fuzzy systems with parametric uncertainties is developed. The uncertain TS fuzzy system is represented as an uncertain multiple linear system. The control problem of TS fuzzy system is converted into the stabilization problem of a uncertain multiple linear system. A sufficient condition for robust stabilization is obtained in terms of linear matrix inequalities (LMI). A Design example is illustrated to show the effectiveness of the proposed method.