• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.60-66
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• 1996

Brushless DC(BLDC) motor have been increasingly used in machine tools and robotics applications due to the reliability and the efficiency. In control of BLDC motor, it is important to construct the controller which is robust to parameter variations and external disturbances. Variable structure controller(VSC) has been known as a powerful tool in robust control of time varying systems. In practical systems, however, VSC has a high frequency chattering which deteriorates system performances. In this paper, a binary controller(BC) which takes the form of VSC and MRAC combined is presented to solve this problem. BC consists of the primary loop controller and the external loop controller to change the gain of primary loop controller smoothly. So it can generate the continuous control input and is insensitive to parameter variations in the given domain. To confirm the validity, various investigations of control characteristics for various design parameters in a position control system of BLDC motor are carried out. (author). 11 refs., 18 figs., 1 tab.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1076-1079
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• 1993

A fuzzy digital controller is combined an autopilot system for compensating the cross coupling effect of the induced roll due to the dynamic characteristic of three fin torpedo. However the utilization of fuzzy chip has many interfacing problems with typical microprocessors of the guidance and control unit. Since a fuzzy digital controller on a microprocessor uses a finite word length A/D converters arul D/A converters, ADC and DAC may generate nonlinear effects such as deadband and limit cycle phenomena. In this paper, the robustness of fuzzy digital controller is tested with ADC a finite word length.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1080-1085
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• 1993

A nonlinear control algorithm for the depth control of underwater vehicles is presented. In order to consider the deadzone effect of the flow control valve, a nonlinear fuzzy logic controller (FLC) is synthesized and combined with a linear proportional-derivative-acceleration (PDA) controller, which is called, the PDA/FLC controller. And, to show the effectiveness of the PDA/FLC control system, it is compared with the linear PDA control system through computer simulation. It is found that the PDA/FLC control scheme is a suitable one to maintain the desirable depth of underwater vehicles with deadzone.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.197-203
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• 1997

In this paper, we present a GP-PID(Generalized Predictive PID) controller which has the same structure as a generalized predictive control with steady-state weighting. The proposed controller can perform better than the conventional PID controller because it includes intrinsic delay-time compensator. The PID tuning parameters and delay-time compensator are calculated by equating the two degree of freedom PID to a linear form of GPC. The proposed controller is combined with a supervisor for safe start and self-tuning. GP-PID controller has been tested for various numerical models and an experimental stirred tank heater. As a result, it was observed that the proposed controller shows a satisfactory performance for variable delay as well as stochastic disturbance.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2573-2576
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• 2003

This paper proposes the controller for biped robot using intelligent control algorithm. The main purpose of this paper is to design the robot controller using Hierarchical Mixture of Experts(HME). The neural network direct control method will be applied to the control scheme for the biped robot and neural network will learn the dynamics of biped robot. The teaming scheme using a intelligent controller to biped robot is developed. The teaming scheme uses a HME controller combined with a inverse biped robot model. The controller provides the control signals at each control time instant. Simulation results are reported for a seven-link biped robot.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.782-784
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• 1999

This paper deals with speed control of DC-servo motor using a Back-Propagation(BP) Learning Algorism and a PID controller Conventionally in the industrial control, PID controller has been used. But the PID controller produced suitable parameter of each system and also variable of PID controller should be changed enviroment, disturbance, load. So this paper revealed for experimental, a neural network and a PID controller combined system using developed speed characters of a Variable Load DC-servo motor. The parameters of the plant are determined by neural network perform on on-line system after training the neural network on off-line system.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.256-262
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• 2000

This paper proposes a new sliding mode controller combined with a multi-layer neural network using the error back propagation learning algorithm,, The network acts as a compensator of the conventional sliding mode controller to improve the control performance when initial assumptions of uncertainty bounds of system parameters are violated. The proposed controller can reduce th steady state error of conventional sliding mode controller with the boundary layer technique Computer simulation results show that the proposed method is effective to control dynamic systems with unexpectably large uncertainties.

• Journal of Power System Engineering
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• v.19 no.4
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• pp.24-29
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• 2015

This paper designs a looper-tension controller for strip top-tail parts in hot strip finishing mills. A three-degree linear model of the looper-tension system is derived by a Taylor's linearization method, where the actuator's dynamics are ignored because of their fast responses. A feedforward shaping controller for the strip top part and a feedforward model reference controller for the strip tail part are respectively designed, they are combined with an ILQ(Inverse Linear Quadratic optimal control) feedback controller for the strip middle part. It is shown from by a computer simulation that the proposed controller is very effective to the strip top-tail parts including the middle part.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.228-231
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• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.