• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.37-47
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• 1998

This paper proposes a controller design method using the evolutionary computation algorithm and the fuzzy logic to control the wafer temperature in rapid thermal processing. First, we design the feedforward static controller to provide the control powers of the lamps for the given steady state temperature. Second, the feedforward dynamic controller is designed for the additional control powers to achieve a given transient response. These feedforward controllers are implemented by using the fuzzy logic to act as a global nonlinear controller over a wide range of operating points. The parameters of these controllers are optimized by using the evolutionary computation algorithm so that it can be used when the mathematical model is not available. In addition, the feedback error controller is introduced to compensate the feedforward controllers when there exist disturbances and modeling errors. The gain of feedback error controller is also obtained by the evolutionary computation algorithm. Through simulations, we verify the proposed control system can give a satisfactory performance.

• Journal of KSNVE
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• v.8 no.3
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• pp.441-449
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• 1998

A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.2
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• pp.19-25
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• 2005

In this paper, the feedforward control with least mean square (LMS) adaptive algorithm is proposed and examined to reduce rotating error by runout of an active magnetic bearing system. Using eddy-current type gap sensors for control, the electrical runout caused by non-uniform material properties of sensor target produces rotational error amplified in feedback control loop, so this runout should be eliminated to increase rotating accuracy. The adaptive feedforward controller is designed and examined its tracking performances and stability numerically with established frequency response function. The designed feedforward controller was applied to a grinding spindle system which is manufactured with a 5.5 kW internal motor and 5-axis active magnetic bearing system including 5 eddy current gap sensors which have approximately 15∼30㎛ of electrical runout. According to the experimental results, the error signal in radial bearings is reduced to less than 5 ,Urn when it is rotating up to 50,000 rpm due to applying the feedforward control for first order harmonic frequency, and corresponding vibration of the spindle is also removed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.415-420
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• 2009

This paper presents a position tracking control of a flexible beam using the piezoelectric actuator. This is achieved by implementing both feedforward hysteretic compensator of the actuator and PID feedback controller. The Preisach model is adopted to develop the feedforward hysteretic compensator. In the design of the compensator, estimated displacement of the piezoceramic actuator is used on the basis of the limiting triangle database that results from collecting data of the main reversal curve and the first order ascending curves. Experimental implementation is conducted for position tracking control and performance comparison is made between a PID feedback controller without considering the effect of hysteresis, and a PID feedback controller integrated with the feedforward hysteretic compensator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.319-322
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• 1996

Automatic gauge control algorithm in rolling process is composed of several functions. Among them feedforward control method is used to compensate irregularity of input strip thickness before rolling process. Since it's very difficult to get an explicit relation between the degree of irregularity of input strip and manipulated variables, approximate linear equation like straight line is used in real system. Furthermore parameters included in such static equation should be changed by characteristics of input strip and modified by roll states. Despite this problem, rolling process use variables in feedfroward controller as a constant. Therefore this problem increases the possibilities of irregularity of thickness control. This paper presents an algorithm which can properly infer present states of process and intelligently manipulate the parameter of feedforward controller.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.4
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• pp.11-19
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• 1996

Recently, fuzzy and neural network techniques have been successfully applied to control of complex and ill-defined system in a wide variety of areas, such as robot, water purification, automatic train operation system and automatic container crane operation system, etc. In this paper, we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feedforward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand, feedforward neural networks provide salient features, such as learning and parallelism. In the proposed neuro-fuzzy controller, the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error backpropagation algorithm as a learning rule, while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally, the effectiveness of the proposed controller is verified through computer simulation of an inverted pendulum system.

• Journal of IKEEE
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• v.17 no.1
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• pp.83-88
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• 2013

This paper presents the output feedback control design for feedforward nonlinear systems with input and output delay. The proposed output feedback controller is composed of a linear observer and a linear controller. It is shown that by using Lyapunov-Krasovskii theorem, the proposed controller ensures a global asymptotic stability for arbitrarily large delay. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• 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.