• Title/Summary/Keyword: Fuzzy Analysis

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Design of Optimized Fuzzy Cascade controller Based on Partical Swarm Optimization for Ball & Beam System (볼빔 시스템에 대한 입자 군집 최적화를 이용한 최적 퍼지 직렬형 제어기 설계)

  • Jang, Han-Jong;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.12
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    • pp.2322-2329
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    • 2008
  • In this study, we introduce the design methodology of an optimized fuzzy cascade controller with the aid of particle swarm optimization(PSO) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. We introduce the fuzzy cascade controller scheme which consists of the outer(1st) controller and the inner(2nd) controller as two cascaded fuzzy controllers, and auto-tune the control parameters(scaling facrors) of each fuzzy controller using PSO. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on PSO, is presented in comparison with the conventional PD cascade controller based on serial genetic alogritms.

Analysis and Tuninig of Scaling Factors of Fuzzy Logic Controller (퍼지논리 제어기의 scaling factor의 분석 및 동조)

  • Lee, Chul-Heui;Kim, Kwang-Ho
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.717-719
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    • 1995
  • In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller and propose the tuning method for them. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. An approximate transfer function of a fuzzy controller is derived from the comparison a fuzzy controller with the conventional PID controller. We analyze the effects of scaling factor using this approximate transfer function and propose a fuzzy tuning method based on that of Maeda et al[4].

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A novel story on rock slope reliability, by an initiative model that incorporated the harmony of damage, probability and fuzziness

  • Wang, Yajun
    • Geomechanics and Engineering
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    • v.12 no.2
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    • pp.269-294
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    • 2017
  • This study aimed to realize the creation of fuzzy stochastic damage to describe reliability more essentially with the analysis of harmony of damage conception, probability and fuzzy degree of membership in interval [0,1]. Two kinds of fuzzy behaviors of damage development were deduced. Fuzzy stochastic damage models were established based on the fuzzy memberships functional and equivalent normalization theory. Fuzzy stochastic damage finite element method was developed as the approach to reliability simulation. The three-dimensional fuzzy stochastic damage mechanical behaviors of Jianshan mine slope were analyzed and examined based on this approach. The comprehensive results, including the displacement, stress, damage and their stochastic characteristics, indicate consistently that the failure foci of Jianshan mine slope are the slope-cutting areas where, with the maximal failure probability 40%, the hazardous Domino effects will motivate the neighboring rock bodies' sliding activities.

The Prediction of Self-Excited Oscillation of a Fuzzy Control System Based on the Describing Function - Static Case (묘사함수를 이용한 퍼지 제어 시스템의 자기진동 현상의 예측 - 정적 경우)

  • 김은태;노흥식;김동연;박민용
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.3
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    • pp.90-96
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    • 1998
  • The self-excited oscillation is the phenomenon which can be observed in the systems composed of nonlinear elements. The phenomenon is of fundamental importance in nonlinear systems and, as far as the design of a nonlinear system is concerned, it should be considered along with the stability analysis. In this paper, the oscillation of a system controlled by a static nonlinear fuzzy controller is theoretically addressed. First, the describing functionof a static fuzzy controller is derived and then, based on the derived describing function, self-excited oscillation of the system controlled by a static fuzzy controller is predicted. To obtain the describing function of the static fuzzy controller, a simple struture is assumed for the fuzzy controller. Finally, computer simulation is included to show an example where the describing function given in the paper is used to predict the self-excited oscillation of a fuzzy-control system.

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A New Fuzzy Logic based Modeling and Simulation of a Switched Reluctance Motor

  • Wadnerkar, Vikas S.;Bhaskar, Mithun M.;Das, Tulasi Ram;RajKumar, A.D.
    • Journal of Electrical Engineering and Technology
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    • v.5 no.2
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    • pp.276-281
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    • 2010
  • The switched reluctance motor (SRM) is an older member of the electric machines family. Its simple structure, ruggedness and inexpensive manufacturing potential make it extremely attractive for industrial applications. However, these merits are overshadowed by its inherent high torque ripple, acoustic noise and difficulty to control. In this paper, a control strategy of the angle position control for the SRM drive based on fuzzy logic is illustrated. The input control parameter, the output control parameter and fuzzy control with FAM table formulation strategy are described and simulated with control patterns, and the decision form of the fuzzy control is illustrated and simulated, and the scope of implementing in a Fuzzy based ASIC chip is enlightened with literature support.

Multisensor Data Combination Using Fuzzy Weighted Average (퍼지 가중 평균을 이용한 다중 센서 데이타 융합)

  • Kim, Wan-Joo;Ko, Joong-Hyup;Chung, Myung-Jin
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.383-386
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    • 1993
  • In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.

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Fuzzy Preference Based Interactive Fuzzy Physical Programming and Its Application in Multi-objective Optimization

  • Zhang Xu;Huang Hong-Zhong;Yu Lanfeng
    • Journal of Mechanical Science and Technology
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    • v.20 no.6
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    • pp.731-737
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    • 2006
  • Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer.

Design and Analysis of Fuzzy Control in a Variable Speed Refrigeration System

  • Hua, Li;Jeong, Seok-Kwon
    • International Journal of Air-Conditioning and Refrigeration
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    • v.15 no.2
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    • pp.61-69
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    • 2007
  • This paper deals with fuzzy control with a feedforward compensator to progress both energy saving and coefficient of performance (COP) in a variable speed refrigeration system. Both the capacity and superheat are controlled simultaneously and independently in the system. By adopting the fuzzy theory, the controller design for the capacity and superheat is possible without depending on a dynamic model of the system. Moreover, the feedforward compensator of the superheat can reduce influence of the interfering loop between the capacity and superheat. Some experiments are conducted to design appropriate fuzzy controller by an iteration manner. The results show that the proposed fuzzy controller with the compensator can establish good control performances for the complicated refrigeration system in spite of its inherent strong non-linearity. Also, the fuzzy control performances were investigated by comparing to the model based PI control experimental results to evaluate transient behavior under the control.

Intelligent algorithm and optimum design of fuzzy theory for structural control

  • Chen, Z.Y.;Wang, Ruei-Yuan;Meng, Yahui;Chen, Timothy
    • Smart Structures and Systems
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    • v.30 no.5
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    • pp.537-544
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    • 2022
  • The optimal design of structural composite materials is a research topic that attracts the attention of lots researchers. For many more thirty years, there has been increasing interest in the applications in all kinds of topics, which means taking advantage of fuzzy set theory, fuzzy analysis, and fuzzy control for designing high-performance and efficient structural systems is a fundamental concern for engineers, and many applications require the use of a systems approach to combine structural and active control systems. Therefore, an intelligent method can be designed based on the mitigation method, and by establishing the stable of the closed-loop fuzzy mitigation system, the behavior of the closed-loop fuzzy mitigation system can be accurately predicted. In this article, the intelligent algorithm and optimum design of fuzzy theory for structural control has been provided and demonstrated effective and efficient in practical engineering issues.