• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.780-785
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• 2007

This paper proposes the decentralized dynamic output feedback controller for discrete-time nonlinear interconnected systems using Takagi-Sugeno (T-S) fuzzy model. Through T-S fuzzy model of each subsystem, the decentralized dynamic output feedback controller is designed. By the closed-loop subsystems with controller, it represents the linear matrix inequality (LMI) for stability of whole interconnected system. The value of control gain are obtained by LMI. An example is given to show the experimentally verification discussed throughout the paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.149-152
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• 2001

본 논문은 연속 시간과 이산 시간에서의 스위칭 모드 퍼지 모델 기반 제어기의 새로운 설계 기법에 대해서 논의한다. 스위칭 모드 퍼지 모델 기반 제어기의 설계에는 Takagi-Sugeno(75) 퍼지 시스템이 사용된다. 이 스위칭 모드 퍼지 모델 기반 제어기는 "정복-분할(divide and conquer)"이라는 하향식 접근 방식을 이용한다. 이 방법은 여러 개의 규칙을 가지고 있는 시스템에서 유한의 하위 시스템으로 시스템을 분할하여 각각의 부분 해를 구하고 이들을 결합하여 전체 시스템의 해를 구하는 방법이다. 제어기의 설계 조건은 주어진 75 퍼지 시스템의 안정화를 보장하는 선형 행렬 부등식들(LMls)에 의해 결정된다. 적절한 시뮬레이션 예제를 통한 성능 비교를 통해 본 논문의 우수성을 입증한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.110-121
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• 1997

Stability issues of linear Takagi-Sugeno fuzzy modles are thoroughly investigated. At first, a systematic way of searching for a common symmetric positive definite P matrix (common P matrix in short), which is related to stability, is proposed for N subsystems which are under a pairwise commutativity assumption. Robustness issue under modeling uncertainty in each subsystem is then considered by proposing a quadratic stability criterion and a method of determining uncertainty bounds. Finally, it is shown that the pairwise commutative assumption can be in fact relaxed by interpreting the uncertainties as mismatch parts of non-commutative system matrices. Several examples show the validity of the proposed methods.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.145-155
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• 2010

This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.240-250
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• 2015

The development of the control algorithms for under-actuated systems is important. Decoupled sliding mode control has been successfully employed to control under-actuated systems in a decoupling manner with the use of sliding mode control. However, in such a control scheme, the system functions must be known. If there are uncertainties in those functions, the control performance may not be satisfactory.In this paper, the direct adaptive fuzzy sliding mode control is employed to control a class of under-actuated uncertain systems which can be regarded as a combination of several subsystems with one same control input. By using the hierarchical sliding control approach, a sliding control law is derived so as to make every subsystem stabilized at the same time. But, since the system considered is assumed to be uncertain, the sliding control law cannot be readily facilitated. Therefore, in the study, based on Lyapunov stable theory a fuzzy compensator is proposed to approximate the uncertain part of the sliding control law. From those simulations, it can be concluded that the proposed compensator can indeed cope with system uncertainties. Besides, it can be found that the proposed compensator also provide good robustness properties.

• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.459-464
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• 2008

In this paper, we present the model-based fuzzy controller for container cranes which effectively performs set-point tracking control of trolley and anti-swaying control under system parameter and disturbance changes. The first part of this paper focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear model of a container crane. In the second part, we present a design methodology of the model-based fuzzy controller. Sub-controllers are designed using LQ control theory for each subsystem in fuzzy model and then the proposed controller is performed with the combination of these sub-controllers by fuzzy IF-THEN rules. In the results of simulation, the fuzzy model showed almost similar dynamic characteristics compared to the outputs of the nonlinear container crane model. Also, the model-based fuzzy controller showed not only the fast settling time for the change in parameter and disturbance, but also stable and robust control performances without any steady-state error.

• Transactions on Electrical and Electronic Materials
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• v.15 no.6
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• pp.297-304
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• 2014

Due to the nonlinearity and complexity of the three-phase photovoltaic inverter, we propose an intelligent control based on fuzzy logic and the classical proportional-integral-derivative. The feedback linearization method is applied to cancel the nonlinearities, and transform the dynamic system into a simple and linear subsystem. The system is transformed from abc frame to dq0 synchronous frame, to simplify the state feedback linearization law, and make the close-loop dynamics in the equivalent linear model. The controls improve the dynamic response, efficiency and stability of the three-phase photovoltaic grid system, under variable temperature, solar intensity, and load. The intelligent control of the nonlinear characteristic of the photovoltaic automatically varies the coefficients $K_p$, $K_i$, and $K_d$ under variable temperature and irradiation, and eliminates the oscillation. The simulation results show the advantages of the proposed intelligent control in terms of the correctness, stability, and maintenance of its response, which from many aspects is better than that of the PID controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.221-227
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• 2007

This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.171-180
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• 2014

In this paper, a multiple sliding surface (MSS) controller for a twin rotor multi-input-multioutput system (TRMS) with mismatched model uncertainties is proposed. The nonlinear terms in the model are regarded as model uncertainties, which do not satisfy the standard matching condition, and an MSS control technique is adopted to overcome them. In order to control the position of the TRMS, the system dynamics are pseudo-decomposed into horizontal and vertical subsystems, and two MSSs are separately designed for each subsystem. The stability of the TRMS with the proposed controller is guaranteed by the Lyapunov stability theory. Some simulation results are given to verify the proposed scheme, and the real time performances of the TRMS with the MSS controller show the effectiveness of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.227-237
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• 1997

Autonomous Underwater Vehicles(AUVs) have become an important tool for various purposes in subsea: inspection, recovery, construction, etc., and the development of autonomous control system is luglay desirable- thete zffe many problems associated with designing the control system for AUV due to unknown underwater envimn-Tnent, the possibility of subsystem failures, and unpredictable changes in the dynamics of the vehicle. In this paper, an autonomous control system based on the intelligent control theory to enhance operation efficiency of the ALTV is presented. The control system has a hierarchical structure which consists of mission planning level, mission control level, navigation level, and execution level. The performance of the control system is investigated by computer simulation. The results show that the proposed control system can be applied successfully to the AUV in spite of the possibility of failures in the vehicle and the collision hazard in the sea environment.