• Journal of Power Electronics
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• 제12권2호
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• pp.294-304
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• 2012

This paper proposes a fuzzy speed tracking controller and a fuzzy rotor angular acceleration observer for a surface-mounted permanent magnet synchronous motor (SPMSM) based on the Takagi-Sugeno (T-S) fuzzy model. The proposed observer-based controller is robust to load torque variations since it utilizes rotor angular acceleration information instead of the load torque value. Linear matrix inequality (LMI) sufficient conditions are given to compute the gain matrices of the speed tracking controller and the observer. In addition, it is mathematically verified that the proposed observer-based control system is asymptotically stable. Simulation and experimental results are presented to confirm that the proposed control algorithm assures a better transient behavior and less sensitivity under model parameter variations than the conventional PI control method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.149-152
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• 2005

In this paper, a robust $H\infty$ stabilization problem to a uncertain discrete-time fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi -Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H\infty$ controllers are given in terms of linear matrix inequalities.

• 한국지능시스템학회논문지
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• 제11권6호
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• pp.459-464
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• 2001

본 논문에서는 마코비안 압력 지연을 갖는 TS 퍼지 시스템의 확률적 안정화 방법을 제안한다. 유한 마코브프로세스는 전체 제어 시스템의 이력 시간 지연을 모델링하기 위해 채용된다. 또한, ZOH 장치는 제어 입력의 이산화에 이용된다고 가정한다. 마코프 입력 지연을 갖는 연속 시간 TS 퍼지 시스템은 지연을 쉽게 조작하기 위해 이산화 된다. 따라서 이산화된 TS 퍼지시스템은 점프 파라미터를 갖는 이산 시간 TS 퍼지시스템을 나타내어 진다. 점프 TS 퍼지시스템의 확륙적 안장화는 선형 행렬 부등식에 의해 유도되고 공식화된다.

• Journal of information and communication convergence engineering
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• 제8권6호
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• pp.702-708
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• 2010

This paper proposes a novel linearization method for Takagi.sugeno (TS) fuzzy model. A T-S fuzzy controller consists of linear controllers based on local linear models and the local linear controllers cannot be designed independently because of overall stability conditions which are usually conservative. To use linear control theories easily for T-S fuzzy system, the linearization of T-S fuzzy model is required. However, The linearization of T-S fuzzy model is difficult to be achieved by using existing linearization methods because fuzzy rules and membership functions are included in T-S fuzzy models. So, a new linearization method is proposed for the T-S fuzzy system based on the idea of T-S fuzzy state transformation. For the T-S fuzzy system linearized with uncertainties, a robust optimal controller with the robustness of sliding model control(SMC) is designed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2393-2398
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• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

• 동력기계공학회지
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• 제2권2호
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• pp.47-54
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• 1998

Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.524-526
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• 1999

In the construction of successful fuzzy models and/or controllers for nonlinear systems, the identification of a good fuzzy inference system is an important yet difficult problem, which is traditionally accomplished by a time-consuming trial-and-error process. In this paper, we propose a systematic identification procedure for complex multi-input single-output nonlinear systems with DNA coding method. A DNA coding method is optimization algorithm based on biological DNA as conventional genetic algorithms(GAs) are. The strings in the DNA coding method are variable-length strings, while standard GAs work with a fixed-length coding scheme. the DNA coding method is well suited to learning because it allows a flexible representation of a fuzzy inference system. We also propose a new coding method fur applying the DNA coding method to the identification of fuzzy models. This coding scheme can effectively represent the zero-order Takagi-Sugeno(TS) fuzzy model. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a Duffing-forced oscillation system.

• 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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.141-144
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• 2001

This paper proposes a decentralized control technique for 2-dimensional experimental helicopter systems. The decentralized control technique is especially suitable in large-scale control systems. We derive the stabilization condition for the interconnected Takagi-Sugeno (75) fuzzy system using the rigorous tool - Lyapunov stability criterion and formulate the controller design condition in terms of linear matrix inequality (LMI). To demonstrate the feasibility of the proposed method, we include the experiment result as well as a computer simulation one, which strongly convinces us the applicability to the industry.

• 한국지능시스템학회논문지
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• 제13권1호
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• pp.85-90
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• 2003

본 논문에서는 퍼지모델을 이용하여 비선형 시스템을 위한 적응 PID 제어기 설계 방법을 제안한다. TSK 퍼지모델을 이용하여 제어 입력의 오차를 예측하고 그 오차로부터 PID제어기의 파라미터를 적응시킨다. TSK 퍼지모델 또한 플랜트의 실제 출력과 모델 출력을 비교하여 모델 파라미터의 적응이 가능하도록 하였다. 제안된 방법으로 비선형의 플랜트에 대한 모호성, 파라미터의 변화 등에 적응할 수 있는 PID 제어기의 설계가 가능하였다. 그리고 몇 개의 비선형 시스템에 대한 시뮬레이션으로 제안된 알고리즘의 유용성도 확인되었다.