• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.81-85
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• 2010

This paper deals with the issue of motion control of a single rod cylinder-load system using simple adaptive control (SAC) method. Prior to controller design, the experiment of open-loop response has been performed. Based on it, design parameters of transfer function are obtained. The effect of parallel feedforward compensator has been investigated by computer simulation, suppressing the oscillatory motion. Through experiments it is conformed that the SAC method gives good tracking performance compared to the PD control method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.188-195
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• 2002

We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLS[10] for three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[10].

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2992-2994
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• 1999

This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the weight adjustment is developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Also, the tracking errors between the system outputs and the desired outputs converge to zero asymptotically. To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.485-488
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of ruler from human operators. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.263-266
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• 1998

This paper propose a prefilter type inverse control algorithm using chaotic neural networks. Since the chaotic neural networks show robust characteristics in approximation and adaptive learning for nonlinear dynamic system, the chaotic neural networks are suitable for controlling robotic manipulators. The structure of the proposed prefilter type controller compensate velocity of the PD controller. To estimate the proposed controller, we implemented to the Cartesian space control of three-axis PUMA robot and compared the final result with recurrent neural network(RNN) controller.

• Journal of Navigation and Port Research
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• v.33 no.5
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• pp.323-330
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• 2009

We have been developing an underwater robot for harbour construction using a parallel mechanism The robot is attached to the rope of a crane, which curries a large stone into the undersea The robot's yaw and pitch are controlled by hydraulic cylinders but its roll is uncontrollable. We mount propellers in both side of the robot to generate the roll motion This paper studies on the control for the roll motion of a underwater robot. A gyro-sensor is used to measure the angle in a roll motion We develop the dynamic model to describe the robot's roll motion by a second order non-linear system and identify the model parameters by recursive least square and adaptive identifier. PD control, recursive model based control and adaptive model based control are applied with the dynamic model which computes the control input to compensate disturbances. This paper introduces the underwater robot system and presents the simulated and experimental results of the proposed controller.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.702-704
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• 1997

In this paper, we applied self-tuning controller with I-PD type to process with time delay's. Process parameters are estimated by the recursive least squares algorithm, and optimal gains are obtained. This paper shows self-tuning controller with I-PD type performs better than that of general PID type for the nonlinear system with sudden change of set-points.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.1-12
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• 1999

A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.131-136
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• 2003

Five expensive sensors are necessary to control a magnetic bearing system. The sensor price rate of magnetic bearing system is high. So it is necessary that cheap and good sensor is developed. The optical fiber displacement sensor is adaptive to satisfy this condition. We can design magnetically suspended spindle based on static characteristic of optical fiber displacement sensor developed. The controller can be designed by decoupled feedback PD. Therefore, it is simpler than any other controller comparatively.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.563-569
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• 2015

A chemical reaction occurring in CSTR (Continuous Stirred Tank Reactor) is significantly affected by the concentration, temperature, pressure, and reacting time of materials, and thus it has strong nonlinear and time-varying characteristics. Also, when an existing linear PID controller with fixed gain is used, the performance could deteriorate or could be unstable if the system parameters change due to the change in the operating point of CSTR. In this study, a technique for the design of a fuzzy PD plus I controller was proposed for the temperature control of a CSTR process. In the fuzzy PD plus I controller, a linear integral controller was added to a fuzzy PD controller in parallel, and the steady-state performance could be improved based on this. For the fuzzy membership function, a Gaussian type was used; for the fuzzy inference, the Max-Min method of Mamdani was used; and for the defuzzification, the center of gravity method was used. In addition, the saturation state of the actuator was also considered during controller design. The validity of the proposed method was examined by comparing the set-point tracking performance and the robustness to the parameter change with those of an adaptive controller and a nonlinear proportional-integral-differential controller.