• Title/Summary/Keyword: weighting fuzzy set

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PID control with parameter scheduling using fuzzy logic

  • Kwak, Jae-Hyuck;Jeon, Gi-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.449-454
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    • 1994
  • This paper describes new PID control methods based on the fuzzy logic. PID gains are retuned after evaluating control performances of transient responses in terms of performance features. The retuning procedure is based on fuzzy rules and reasoning accumulated from the knowledge of experts on PID gain scheduling. For the case that the retuned PID gains result in worse CLDR (characteristics of load disturbance rejection) than the initial gains, an on-line tuning scheme of the set-point weighting parameter is, proposed. This is based on the fact that the set-point weighting method efficiently reduce either overshoot or undershoot without any degradation of CLDR. The set-point weighting parameter is adjusted at each sampling instant by the fuzzy rules and reasoning. As a result, better control performances were achived in comparison with die controllers tuned by the Z-N (Ziegler-Nichols) parameter tuning formula or by the fixed set-point weighting parameter.

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Weighted fuzzy controller composed of position type fuzzy controller and velocity type fuzzy controller (위치형퍼지제어기와 속도형퍼지제어기로 구성된 퍼지 가중치 제어기)

  • 김병수;박준열
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.181-183
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    • 1996
  • Generally, While position type fuzzy controller has good performance in transient period, it has uniform steady state error of response. While velocity type fuzzy controller is capable of reducing steady state error of response, it is hard to develop the performance in transient period. In order to have both good performance in transient period and ability to reduce the steady state error of response, weighting fuzzy controller, which is composed of these two fuzzy controllers, is proposed. For the decision of weight to each fuzzy controller, Weighting fuzzy set is established according to the system state variables and applied to each fuzzy controller. The proposed weighted fuzzy controller has the merits of both position type fuzzy controller and velocity type fuzzy controller simultaneously.

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Weighting objectives strategy in multicriterion fuzzy mechanical and structural optimization

  • Shih, C.J.;Yu, K.C.
    • Structural Engineering and Mechanics
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    • v.3 no.4
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    • pp.373-382
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    • 1995
  • The weighting strategy has received a great attention and has been widely applied to multicriterion optimization. This gaper examines a global criterion method (GCM) with the weighting objectives strategy in fuzzy structural engineering problems. Fuzziness of those problems are in their design goals, constraints and variables. Most of the constraints are originated from analysis of engineering mechanics. The GCM is verified to be equivalent to fuzzy goal programming via a truss design. Continued and mixed discrete variable spaces are presented and examined using a fuzzy global criterion method (FGCM). In the design process a weighting parameter with fuzzy information is introduced into the design and decision making. We use a uniform machine-tool spindle as an illustrative example in continuous design space. Fuzzy multicriterion optimization in mixed design space is illustrated by the design of mechanical spring stacks. Results show that weighting strategy in FGCM can generate both the best compromise solution and a set of Pareto solutions in fuzzy environment. Weighting technique with fuzziness provides a more relaxed design domain, which increases the satisfying degree of a compromise solution or improves the final design.

Fuzzy Indexing and Retrieval in CBR with Weight Optimization Learning for Credit Evaluation

  • Park, Cheol-Soo;Ingoo Han
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.491-501
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    • 2002
  • Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

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Optimization of Fuzzy Systems by Means of GA and Weighting Factor (유전자 알고리즘과 하중값을 이용한 퍼지 시스템의 최적화)

  • Park, Byoung-Jun;Oh, Sung-Kwun;Ahn, Tae-Chon;Kim, Hyun-Ki
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.6
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    • pp.789-799
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    • 1999
  • In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

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The Fuzzy Ziegler-Nichols Tuning Method for PID Controller (PID 제어기의 퍼지 Ziegler-Nichols 동조 방법)

  • 최정내;이원혁;김진권;황형수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.03a
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    • pp.43-46
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    • 1998
  • This paper presents a new parameter tuning method for PID controller. The Ziegler-Nichols Parameter tuning has been widely known as a fairly heuristic method to good determine setting of PID controllers, for a wide range of common industrial processes It has a excessive overshoot in the set point response, set point weighting can reduced the overshoot to specified values. It will also be shown that set point weighting is superior to the conventional solution of reducing large overshoot by other method. In this paper, we will modified the Ziegler-Nichols tuning formula by fuzzy set. These method will give appreciable improvement in the performance of PID controllers.

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Methods of pairwise comparisons and fuzzy global criterion for multiobjective optimization in structural engineering

  • Shih, C.J.;Yu, K.C.
    • Structural Engineering and Mechanics
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    • v.6 no.1
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    • pp.17-30
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    • 1998
  • The method of pairwise comparison inherently contains information of ambiguity, fuzziness and conflict in design goals for a multiobjective structural design. This paper applies the principle of paired comparison so that the vaguely formulated problem can be modified and a set of numerically acceptable weight would reflect the relatively important degree of multiple objectives. This paper also presents a fuzzy global criterion method ($FGCM_{\lambda}$) included fuzzy constraints that coupled with the objective weighting rank obtained from the modified pairwise comparisons for fuzzy multiobjective optimization problems. Descriptions in sequence of this combined method and problem solving experiences are given in the current article. Multiobjective design examples of truss and mechanical spring structures illustrate this optimization process containing the revising judgement techniques.

An Optimal Path Generation Method considering the Safe Maneuvering of UGV (무인지상차량의 안전주행을 고려한 최적경로 생성 방법)

  • Kwak, Kyung-Woon;Jeong, Hae-Kwan;Choe, Tok-Son;Park, Yong-Woon;Kwak, Yoon-Keun;Kim, Soo-Hyun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.6
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    • pp.951-957
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    • 2010
  • An optimal path generation method considering the safety of UGV(Unmanned Ground Vehicle) is proposed and demonstrated through examples. Among various functions of UGV, real-time obstacle avoidance is a key issue to realize realistic scenario in FCS(Future Combat Systems). A two-dimensional narrow corridor environment is considered as a test field. For each step of UGV movement, two objectives are considered: One is to minimize the distance to the target and the other to maximize the distance to the nearest point of an obstacle. A weighted objective function is used in the optimization problem. Equality and inequality constraints are taken to secure the UGV's dynamics and safety. The weighting factors are controlled by a fuzzy controller which is constructed by a fuzzy rule set and membership functions. Simulations are performed for two cases. First the weighting factors are considered as constant values to understand the characteristics of the corresponding solutions and then as variables that are adjusted by the fuzzy controller. The results are satisfactory for realistic situations considered. The proposed optimal path generation with the fuzzy control is expected to be well applicable to real environment.

Optimum Design of Rotor System Considering Fuzzy Constraints (퍼지 구속조건을 고려한 회전축계의 최적설계)

  • 양보석;공영모
    • Journal of Advanced Marine Engineering and Technology
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    • v.16 no.5
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    • pp.39-49
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    • 1992
  • The dynamic design object of rotor system is to optimize the system in stability at the operating speed, unbalance response in the vicinity of the rotor critical speed, bearing weighting and system weighting. In conventional optimization method, designers have to set mathematical modeling, such as objective function, constraints and design parameters, strictly and quantitavely. But in actual design process, they do not treat all of these values strictly and some of them are somehow "fuzziness". So, considering boundary conditions of seal diameter, clearance, and length in a typical double suction centrifugal pump is fuzzy, this paper is considered fuzzy in constraints. Fuzzy method is used .alpha.-level cut method. Then, the optimum dimensions of seal according to values are obtained and vibration characteristics are investigated.estigated.

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Dynamic Path Planning for Mobile Robots Using Fuzzy Potential Field Method (퍼지 포텐셜 필드를 이용한 이동로봇의 동적 경로 계획)

  • Woo, Kyoung-Sik;Park, Jong-Hun;Huh, Uk-Youl
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.2
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    • pp.291-297
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    • 2012
  • In this paper, potential field algorithm was used for path planning in dynamic environment. This algorithm is used to plan a robot path because of its elegant mathematical analysis and simplicity. However, there are some problems. The problems are problem of collision risk, problem of avoidance path, problem of time consumption. In order to solve these problems, we fused potential field with fuzzy system. The input of the fuzzy system is set using relative velocity and location of robot and obstacle. The output of the fuzzy system is set using the weighting factor of repulsive potential function. The potential field algorithm is improved by using fuzzy potential field algorithm and, path planning in various environment has been done.