• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.279-286
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• 1996

In this paper, variable structure control(VSC) based on reaching law method with fuzzy inference for nonlinear systems is proposed. The reaching law means the reaching condition which forces an initial state of system to reach switching surface in finite time, and specifies the dynamics of a desired switching function. Since the conventional reaching law has fixed coefficients, the chattering can be existed largely in sliding mode. In the design of a proposed fuzzy reaching law, we fuzzify RP(representative point)'s orthogonal distance to switching surface and RP's distance the origin of the 2-dimensional space whose coordinates are the error and the error rate. The coefficients of the reaching law are varied appropriately by the fuzzy inference. Hence the state of system in reaching mode reaches fastly switching surface by the large values of reaching coefficients and the chattering is reduced in sliding mode by the small values of those. And the effectiveness of the proposed fuzzy reaching law method is showen by the simulation results of the control of a two link robot manipulator.

• 전기학회논문지P
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• 제59권2호
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• pp.163-172
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• 2010

A robust positioning control system has been studied using a friction parameter observer and a recurrent fuzzy neural network based on the sliding model. To estimate a nonlinear friction parameters of the LuGre friction model, a dual friction model-based observer is introduced. In addition, an approximating method for a system uncertainty has been developed using a recurrent fuzzy neural network technique to improve positioning performance. Experimental results have been presented to validate the performance of a proposed intelligent compensation scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1718-1719
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• 2007

In this paper, a fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for manipulators with uncertainties. Especially the system uncertainties is approximated using fuzzy rule adaptation technique. The proposed controller is composed of the equivalent control that includes the approximation of the system uncertainties and the hitting control that is used to constrain the states of the system to maintain on the sliding surfaces and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller

• 한국지능시스템학회논문지
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• 제9권6호
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

• 한국지능시스템학회논문지
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• 제12권2호
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• pp.164-170
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• 2002

슬라이딩 모드 제어방식은 가변구조 제어이론의 하나로서 불확실성을 가진 비선형 시스템에 대한 강인한 특성을 가지고 있지만 제어입력에 채터링 현상을 발생시키기 때문에 그 적용에 한계를 가지고 있다. 채터링을 제거하는 방식에는 여러 가지 방식이 있으나 본 논문에서는 특수한 비선형 함수와 퍼지시스템 이용하여 기존의 고정 경계층 이용방식에 비하여 정상상태 오타를 줄일 수 있는 개선된 채터링 제거전략을 제안한다. 제안된 제어방식에서는 퍼지시스템의 출력변수 상에 설정된 퍼지집합의 구간 범위를 조절함으로써 trade-off관계에 있는 정상상태 오타와 채터링의 크기를 적절히 조절할 수 있다. 제안된 전략의 타당성을 보이기 위해 기존의 고정 경계층 방식을 간단히 분석하고 컴퓨터 시뮬레이션을 통하여 이를 비 교 분석 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.93-99
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• 2003

One of the methods to simplify the design process for a fuzzy logic controller (FLC) is to reduce the number of variables representing the rule antecedent. This in turn decreases the number of control rules, membership functions, and scaling factors. For this purpose, we designed a single-input FLC that uses a sole fuzzy input variable. However, it is still deficient in the capability of adapting some varying operating conditions although it provides a simple method for the design of FLC's. We here design two simple-structured adaptive fuzzy logic controllers (SAFLC's) using the concept of the single-input FLC. Linguistic fuzzy control rules are directly incorporated into the controller by a fuzzy basis function. Thus some parameters of the membership functions characterizing the linguistic terms of the fuzzy control rules can be adjusted by an adaptive law. In our controllers, center values of fuzzy sets are directly adjusted by an adaptive law. Two SAFLC's are designed. One of them uses a Hurwitz error dynamics and the other a switching function of the sliding mode control (SMC). We also prove that 1） their closed-loop systems are globally stable in the sense that all signals involved are bounded and 2） their tracking errors converge to zero asymptotically. We perform computer simulations using a nonlinear plant.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.524-530
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• 2002

본 연구에서는 Sugeno-type 퍼지시스템을 이용하여 계단형 퍼지 이동 슬라이딩 평면을 구성하고 이를 이용한 슬라이딩 모드제어방식을 제안한다 이 퍼지시스템은 위상평면 상에서 상태오차벡터가 이루는 각도와 원점과의 거리를 입력으로 가지며 출력으로 1차 선형방정식을 갖는다. 이 퍼지 슬라이딩 평면을 이용하여 초기 상태를 이 평면상에 위치시키고 이 슬라이딩 평면을 회전시키거나 이동시킴으로써 도달시간을 줄이고 추적시간을 줄인다. 제안된 이동 슬라이딩 평면은 개념적으로 계단형의 이산적인 형태를 가지지만 이 평면이 퍼지시스템으로 구성되기 때문에 연속으로 이동하는 특징을 나타낸다. 제안된 퍼지 슬라이딩 평면에 대한 슬라이딩 모드의 동특성이 안정함을 증명하며 이를 2차 예제시스템을 이용하여 그 타당성을 보인다.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.973-979
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• 2001

Sliding mode control guarantees robustness in the presence of modeling uncertainties and external disturbances. However, this can be obtained at the cost of high control activity that may lead to chattering As one way to alleviate this problem a boundary layer around sliding surface is typically used. In this case the selection of controller gain, control ban width and boundary layer thickness is a crucial problem for the trade-off between tracking error and chattering. The parameter tuning is usually done by trail-and-error in practice causing significant effort and time. An auto tuning method based on fuzzy rules is proposed in the paper in this method tracking error and chattering are monitored by performance indices and the controller tunes the design parameters intelligently in order to compromise both indices. To demonstrate the efficiency of the propose method a mass-spring translation system and a roboic control system are simulated and tested It is shown that the proposed algorithm is effective to facilitae the parameter tuning for sliding mode controllers.

• 한국지진공학회논문집
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• 제3권3호
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• pp.63-74
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• 1999

대형구조물의 진동감소를 위한 슬라이딩 모드 퍼지 제어기(Sliding Mode Fuzzy Control SMFC)에 대하여 연구하였다 본 제어기에 사용된 퍼지 추론기의 규칙은 비선형 제어기법의 하나인 슬라이딩 모드 제어기를 기반으로 하여 구성되었다 그결과 제어기의 퍼지성은 제어시스템을 시스템 계수의 불확실성과 구조물에 작용되는 외부하중의 불확실성에 대하여 강인한 성질은 갖게 하였으며 제어 규칙의 비선형성으로 인하여 제어기는 선형제어기에 비하여 보다 효율적인 되었다 복잡한 수학 해석에 기반한 종래의 제어기법에 비하여 퍼지 이론에 기반한 본 제어기법은 제어기의 설계절차가 매우 편리하다는 장점을 갖게 된다. 제안된 제어기법의 검증을 위하여 미국 토목학회 산하 구조제어위원회(ASCE Committee on Structural Control)에서 주도한 벤치마크 문제에 대하여 적용시켜 보았다 본 연구의 제어결과를 다른 연구자들에 의하여 발표된 {{{{ ETA _mixed _2$\infty$ }}, optimal polynomial control neural networks control 슬라이딩 모드 제어의 벤치마크 결과와 비교하였으며 그 결과 제안된 제어기법이 구조물의 진동을 매우 효율적으로 감소시키며 제어기의 설계절차가 쉽고 편리함을 확일 할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.173-176
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• 1999

This paper shows a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a Polishing robot. Using this method, the number of inference rules and the shape of membership functions are determined by the genetic algorithm. The fuzzy outputs of the consequent part are derived by the gradient descent method. Also, it is guaranteed that .the selected solution become the global optimal solution by optimizing the Akaike's information criterion expressing the quality of the inference rules. It is shown by simulations that the method of fuzzy inference by the genetic algorithm provides better learning capability than the trial and error method.