• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.414-416
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• 1998

One significant error in XY table is due to friction and disturbance. However, the characteristics of this friction is not easy to predict and analyze because of its nonlinearity. Therefore, it is difficult for conventional controller to compensate it effectively. In order to solve this problem, this paper presents a position controller based on fuzzy logic controller(FLC) that is suitable for system with unknown and unmodelled dynamics. The performance of the proposed controller are demonstrated by simulation results.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.672-674
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• 1997

In this paper, we study the idle speed control of the spark ignition engine. Engine idle speed control is a difficult problem because of troublesome characteristics such as severe process nonlinearities, variable time delays, time-varying dynamics and unobservable internal system states and disturbances. We investigate the intelligent control algorithms such as neural network controller and fuzzy controller for 4-cylinder 4-stroke engine.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.158-161
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• 1996

A robust adaptive tracking control architecture is proposed for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty in the dynamics is either unknown or impossible. The architecture employs an adaptive fuzzy system to compensate for the uncertainty of the plant. In order to improve the robustness under approximation errors and disturbances, the proposed architecture includes deadzone in adaptation laws. Unlike the previously proposed schemes, the magnitude of approximate errors and disturbances is not required in the determination of the deadzone size, since it is estimated using the adaptation law. The proposed algorithm is proven to be globally stable in the Lyapunov sense, with tracking errors converging to the proposed architecture.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2756-2759
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• 2000

In this paper. A PID motion controller based on the fuzzy concept is discussed for nonholonomic mobile robot. The difficulties in controlling such a Mobile robot vehicle lies in the fact that it usually has only two degrees of freedom for motion control in a tracking mode. It makes the control of speed and steering possible to decompose the error between the reference posture and the current posture. The Gyro compass is used to measure the position of robot. The proposed nonholonomic mobile robot is shown to follow the reference trajectory and compensate the dynamics. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.145-152
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• 1995

This paper presents a novel SOFLIC(self organizing fuzzy logic intelligent controller) for reactor rod control system in nuclear power plant. The output of fuzzy controller is gener ated by using two signal : the error between reference and average temperature, and the error between reference and neutron flux-converted temperatures. Flexibility of the controller is enhanced by using self-organizing feature and the controller respond to variation of system parameter with more precision. performances of the SOFLIC and PID are simulated with the model developed for a nuclear power plant. The SOFLIC is superior to PID : SOFLIC provides more rapid load following capability. more robustiness for variation in process dynamics and minimization of engineer's mistakes in controller design.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1716-1717
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• 2007

In this paper, a second order fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed sub-controller is composed of the equivalent control that is approximated by an online rule regulation sheme and the hitting control that is used to constrain the states of the sub-system to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.468-471
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• 2003

In this paper, a second order sliding mode control that combines with a fuzzy adaptation technique is presented for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed controller is composed of the equivalent control that is approximated by an online adaptation scheme and the hitting control that is used to constrain the states to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller.

• Earthquakes and Structures
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• v.23 no.4
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• pp.329-338
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• 2022

This work addresses the optimization controller design problem combining the AI evolution bat (EB) optimization algorithm with a fuzzy controller in the practical application of a reinforced concrete frame structure. This article explores the use of an intelligent EB strategy to reduce the dynamic response of Lead Rubber Bearing (LRB) composite reinforced concrete frame structures. Recently developed control units for plant structures, such as hybrid systems and semi-active systems, have inherently non-linear properties. Therefore, it is necessary to develop non-linear control methods. Based on the relaxation method, the nonlinear structural system can be stabilized by properly adjusting the parameters. Therefore, the behavior of a closed-loop system can be accurately predicted by determining the behavior of a closed-loop system. The performance and durability of the proposed control method are demonstrated by numerical simulations. The simulation results show that the proposed method is a viable and feasible control strategy for seismically tuned composite reinforced concrete frame structures.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.1
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• pp.199-208
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• 2001

In this paper, an automatic route tracking algorithm using the position variables and the yaw angle of a ship is suggested, Since most autopilot systems paly only a role of course-keeping by integrating the gyrocompass output, they cannot cope with position errors between the desired route and real route of the ship resulted from a drifting and disturbances such as wave, wind and currents during navigation. In order for autopilot systems to track the desired route, a method which can reduce such position errors is required and some algorithms have been proposed[1,2]While such were turned out effective methods, they have a shortage that the rudder control actions for reducing the position errors are occurred very frequently. In order to improve this problem it is necessary to convert that error into the corresponding yaw angle and necessary to treat only yaw angle control problem. To do this a command generation algorithm which converts the rudder angle command reducing the current position error into they yaw angle command is suggested. To control the ship under disturbances and nonlinearities of the ship dynamics, the adaptive fuzzy controller is developed. Finally, through computer simulations for two ship models, the effectiveness of the suggested method and the possibility of the automatic route tracking are assured.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.670-673
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• 1999

In this paper, we present a robust motion controller based on Adaptive-Fuzzy technique is proposed that multifunctional vehicle(MVR) for two DOF mobile robot can perform detailed inspection of physical conditions of sewage pipes as well as can effectively repair the damaged portions of the inner walls. The main difficulties in controlling this multifunctional robot vehicles lie in the fact that vehicles usually have three degrees of freedom in position and orientation in spite of having only two degrees of freedom for motion control in tracking mode. Decomposition of error between the reference posture and the current posture makes control of speed and steering possible. The Gyro compass part and Inclonometer of the robot is configured in order to realize position of robot. The proposed Adaptive-Fuzzy motion controller has two main characteristics: The one guarantees that the MVR follows the reference trajectory; the other one compensates the dynamics of the MVR. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.