• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.157-157
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• 2000

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. The concept of relative gain matrix is used to obtain the input-output pairs. However, among the input/output variables which are 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 tile introduction of a simple compensator. This compensator adjusts the degree of coupling between variables using a neural network. In this proposed neuro-fuzzy controller, the Neural network which is realized by back-propagation algorithm, adjusts the mutual coupling weight between variables.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.680-688
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• 2001

In this paper, the fuzzy control with variable input gain is applied to maintain the consistent tension in the process of taking up and releasing texture. In the process of discharging web on one side rolling it on another, the take-up drum gets smaller on the release drum side as it gets bigger on the rolling side, thus it is necessary to change the balance of velocity between the sides. In order to solve the problem a tension controller is necessary. The PI control method has been employed to maintain the consistent tension, but the PI control method produces a problem which requires an experienced worker with the traits of the machine, in order to perform the fine adjustments according to the environment of the process. For solving the above problem, we apply fuzzy control to the tension system, in order to produce a uniform roll. For the performance test, the fuzzy controller does not need to revise the parameters. Therefore the fuzzy controller exhibits an excellent additivity for the tension system where the system is changed with time.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.732-735
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• 1997

Variable Structure Controller(VSC) is usually known to have robustness to bounded exogenous disturbances. The robustness is attributed to the discontinuous term in the control input. However, this discontinuous term also causes an undesirable effect called chattering. To alleviate chattering, a hybrid controller consisting of VSC and Fuzzy Logic Controller(FLC) is proposed, which belongs to the category of Fuzzy Sliding Mode Controller(FSMC). The role of FLC in FSMC is to replace a fixed gain of a discontinuous term with a time-varying one based on a specified rule base. The characteristics of proposed controller are shown to be similar to those of VSC with a saturation function instead of sign function. The only remarkable difference is the nonlinearity whose form can be adjusted by free parameters, normalize gain, denormalize gain, and membership functions. Applied to AC servo motor, the proposed controller is compared with VSC in a regulation problem as well as a speed tracking problem. The simulation results show a substantial chatter reduction.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.241-245
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• 1995

This paper shows that the proposed fuzzy-sliding mode for SCARA robot control could reduce chattering problemed in sliding mode control and is robust against parameter uncertainties. It was very small quantities of chattering in the fuzzy-sliding mode control conpared with that in sliding mode control with two dead-band. In here, the sliding mode control with two dead-band is the method to reduce some chattering by changing into a continuous variable lower control input gain when a state value in pahase palne converged sithin two dead-band. But, the fuzzy-sliding mode control for more reducing chattering is the method to change control input by slicing mode into that by fuzzy rule within two dead-band. Simulations show that the effect of reducing chattering by the fuzzy-sliding mode is superior to sliding mode control with two dead-band.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.127-134
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• 2005

This paper proposes a nonlinear fuzzy PID controller with variable parameters to improve slow rising time and divergence occurred by limited input spaces and a resultant limited control input during fuzzification in a fuzzy PID controller with fixed parameters, and describes the design principle and tracking performance of a proposed fuzzy PID controller. The parameters of a proposed controller are adjusted by the stability conditions derived from 'small gain theorem' and satisfy the BIBO stability of overall control system.

• 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.18 no.4
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• pp.488-493
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• 2008

A mathematical model of molten steel level for continuous casting process is presented, where the molten steel level, input and output flow in the mold, the relation between stopper position and input flow etc. are considered. The mathematical model is implemented and simulated by using MATLAB. Comparing the result of molten steel level from the simulator with that of real plant, the performance of the model is shown to be reasonable. By using this simulator, it is shown that PI controller with variable P gain, adjusted by fuzzy logic system, has better control result than conventional PI controller.