• East Asian mathematical journal
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• v.27 no.3
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• pp.289-297
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• 2011

The introduction of fuzzy differential equation is to deal wit fuzzy dynamic systems. As classical differential equations, it is difficult to find the solutions to all fuzzy differential equations. In this paper an existence and uniqueness theorem for linear fuzzy differential equations is obtained. Moreover, the exact solution to linear fuzzy differential equation is given.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.8
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• pp.647-654
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• 2016

Controlling a mobile robot using conventional control devices requires skill and experience, and is not intuitive, especially in complex environments. For human-mobile robot cooperation, the direct-teaching method with impedance control has been used most frequently in complex environments. This thesis proposes a new direct-teaching method for a mobile robot utilizing variable impedance control. This includes analysis of user intention, which is changed by force and moment. A fuzzy inference technique is proposed in this thesis for identification of user intension. The direct teaching of a mobile robot based on variable impedance control through fuzzy inference is experimentally verified by comparing its efficiency to that of the conventional impedance control-based direct teaching of a mobile robot. Experimental data, such as the total time consumed, path error time, and the total energy used by the user, were recorded. The results showed that the efficiency of variable impedance control was increased.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.24-29
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• 2005

In the fuzzy control for the multi-variable system, it is difficult to obtain the fuzzy rule. Therefore, the parallel structure of the independent single input-single output fuzzy controller using a pairing between the input and output variable is applied to the multi-variable system. However, among the input/output variables which arc not paired the interactive effects should be taken into account. these mutual coupling of variables affect the control performance. Therefore, for the control system with a strong coupling property, the control performance is sometimes lowered. In this paper, the effect of mutual coupling of variables is considered by the introduction of a neuro-fuzzy controller using relative gain matrix. This proposed neuro-fuzzy controller automatically adjusts the mutual coupling weight between variables using a neural network which is realized by back-propagation algorithm. The good performance of the proposed nero-fuzzy controller is verified through computer simulations on 200MW boiler systems.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.438-447
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• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• International Journal of Reliability and Applications
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• v.1 no.2
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• pp.123-131
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• 2000

This paper concerns with the consistent estimator for the fuzzy expectation of a random variable taking values in the space F($R^p$) of upper semicontinuous convex fuzzy subsets of $R^p$ with compact support. We introduce the concept of a fuzzy sample mean and show that the fuzzy sample mean is a strong consistent estimator for the fuzzy expectation. Some examples are given to illustrate the main result.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1459-1463
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• 2009

Recently, Zhao et.al [European Journal of Operational Research 169 (2006) 189-201] discussed a random fuzzy renewal process based on random fuzzy theory. They considered the rate of the random fuzzy renewal process and presented a random fuzzy elementary renewal theorem. They also established Blackwell's theorem in random fuzzy sense. But all these results are invalid. We give a counter example in this note.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.195-204
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• 2006

In this paper, we consider a renewal process in which both the inter-arrival times and rewards are fuzzy random variables. We prove the uniform levelwise convergence of fuzzy renewal and fuzzy renewal rewards. These results improve the result of Popova and Wu[European J. Oper. Research 117(1999), 606-617] and the main result of Hwang [Fuzzy Sets and Systems 116 (2000), 237-244].

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.32-44
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• 1997

A moving sliding surface(MSS) was proposed earlier for the second-order variable structure control system(VSCS). The MSS was disigned to pass arbitrary initial conditions, and subsequently moved towards a predetermined sliding surface by rotating and/or shifting. This methodology led to fast and robust control responses of the second-order VSCS, especially in a reaching phase. However, the moving algorithm of the MSS was too complicated to be employed to the high-order VSCS. To resolve this problem, a new moving algorithm based on the fuzzy theory is proposed in this paper. For the generalization of the MSS, the conditions for rotating or shifting are firstly investigated. Then the fuzzy algorithm is formulated by adopting the values of the surface function and the total discontinuity gain as input variables, and the variation of the surface function as output variable. The position control problem of an electrohydraulic servomechanism is adopted in order to demonstrate the efficiency and the feasibility of the proposed MSS associated with fuzzy algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.43-50
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• 1997

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. This makes it very dificult to apply conventional control methods to the combustion control of the refuse. So most of the refuse incineration plant are operated by operators. In this paper, an multi-variable fuzzy model predictive controller is proposed for the combustion control of the re:fuse. Adaptive network based fuzzy inference system is used for modeling of the refuse incineration plant and multi-variable fuzzy model predictive controller is designed based on the identified fuzzy model. And computer simulation was carried out to evaluate performance of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.264-268
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• 2011

This paper presents a Takagi-Sugeno (T-S) type Fuzzy Logic Controller (FLC) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. The parameters are tuned with gradient algorithm. The parameters are changed depending on output. The simulation results demonstrate the usefulness of this T-S type 3 rule fuzzy controller.