• Journal of Power System Engineering
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• v.17 no.5
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• pp.86-93
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• 2013

This paper proposes the used of genetic algorithm for optimizing PI controller and describes the dynamic modeling simulation for the permanent magnet synchronous motor driven by simplified vector control with the aid of MATLAB-Simulink environment. Furthermore, three kinds of error criterion minimization, integral absolute error, integral square error, and integral time absolute error, are used as objective function in the genetic algorithm. The modeling procedures and simulation results are described and presented in this paper. Computer simulation results indicate that the genetic algorithm was able to optimize the PI controller and gives good control performance of the system. Moreover, simplified vector control on permanent magnet synchronous motor does not need to regulate the direct axis component current. This makes simplified vector control of the permanent magnet synchronous motor very useful for some special applications that need simple control structure and low cost performance.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.124-131
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• 1997

This paper presents a modified adaptive control scheme that improves the transient performance of the overall system while maintaining the asymptotic convergence of the output error. The proposed control scheme is characterized as the added outer dynamic feedback loop on the conventional adaptive control scheme. This control scheme enables various robust control methods that were developed for standard model reference adaptive controllers to be applied to the proposed controller. In contrast with the modified adaptive controllers that use augmented errors to provide additional dynamic feedback, the proposed controller uses tracking error directly, thereby reducing the tracking error significantly in the transient state and making the error insensitive to noise.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.115-123
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• 2005

This paper presents the development of an algorithm for position control of feed drives in machine tools. The algorithm is constructed through an experimental method based on proportional control with a ramp input. In the first step of designing, a tracking-error curve is generated with the proportional control, and then an error model is decided to reduce the tracking error, Next, the output signal of the error model is added to the current error signal to yield the actuating error signal. The effectiveness of the proposed scheme is confirmed through simulation and experiments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• Journal of the Korea Safety Management & Science
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• v.8 no.1
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• pp.17-26
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• 2006

Basis frame-work's base in a semiconductor industry have gas, chemical, electricity and various facilities in bring to it. That it is a foundation by fire, power failure, blast, spill of toxicant huge by large size accident human and physical loss and damage because it can bring this efficient, connect with each kind mechanical, physical thing to prevent usefully need that control finding achievement factor of human factor of human action. Large size accident in a semiconductor industry to machine and human and it is involved that present, in system by safety interlock defect of machine is conclusion for error of behaviour. What is not construing in this study, do safety in a semiconductor industry to do improvement. Control human error analyzes in human control with and considers mechanical element and several elements. Also, apply achievement factor using O'conner Model by control method of human error. In analyze by failure mode effect using actuality example.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.636-643
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• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.3 s.168
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• pp.52-60
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• 2005

This paper deals with the position control fur a feed drive system in CNC milling machine, which utilizes a modified error signal for the elimination of steady-state error. A linear time-invariant (LTI) system has consistent properties in response to standard test signal inputs. Those also appear in an error curve acquired from the response. From such properties, constructed is an error model for the position control of the feed drive. And then added is the output of the error model to the current error signal. Consequently the resulting proportional control system brings performance improvement in view of the steady-state error. The effectiveness of the proposed scheme is confirmed through simulations and experiments.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.2
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• pp.168-175
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• 2011

Contouring accuracy of CNC machine tools is very important for high-speed and high-precision machining. In particular, large contour error may occur during corner tracking. In order to reduce the corner contouring error, acceleration and deceleration control or tool-path planning methods have been suggested. However, they do not directly control the corner contouring error. In the meantime, network servo systems are widely used because of their easiness of building and cost effectiveness. Communication latency between the master controller and servo drives, however, may deteriorate contouring accuracy especially during corner tracking. This paper proposes a control strategy that can accurately calculate and directly control the corner contouring error. A prediction control is combined with the above control to cope with communication latency. The proposed control method is evaluated through computer simulation and experiments. The results show its validity and usefulness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.152-157
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• 2000

In the control of CNC machine tools, it is significant for precise machining to reduce the contour error. The object of servo-control is reduction of contour error and tracking error. In past studies, there were two approaches to control a servo-system. One was to eliminate axial tracking errors, and the other was to control contour errors. The Cross-coupled controller(CCC) was introduced fro ma veiwpoint of contour error model. Recently, for machining part with free form surfaces, we propose a new contour error model based on curve interpolator. It is presented here that performance of CCC using proposed model is enhanced. Therefore, we can make more precise parts with the curve interpolator and the new contour error model.

• Journal of Power System Engineering
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• v.22 no.1
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.