• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.241-243
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• 1993

In this paper, a class of neural-network controllers with two inputs of error and error change, is applied to the position control of D.C. servo system. The proposed controller is learned by error back-propagating error information to compensate the weighting value using its previous derivatives and to decrease exponentially a series of self learning coefficients. Through the simulations and implementations, the effectiveness and superiority to the conventional fuzzy controller is proved.

• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.1-6
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• 2010

Direct Drive Valves (DDV) with electric closed loop spool position control are suitable for electrohydraulic position, velocity, pressure or force control systems including those with high dynamic response requirements. The spool drive device is a permanent magnet linear force motor which can actively stroke the spool from its spring centered position in both directions. This basic study is carried out to drive the design parameters for developing a domestic DDV. The static and dynamic characteristics of DDV are examined. The simulation results are compared with data of manufacture's catalog to show the validity of the modelling.

• Journal of Power Electronics
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• v.13 no.1
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3083-3085
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• 1999

This paper presents an algorithm that the mobile robot track accurately a moving object with information from a CCD camera mounted on mobile robot. Singular Value Decomposition is adapted to remove the measurement noise of a Raw data of CCD. The mobile robot estimate the trajectory using Kalman filter and track the path of a moving object with a servo motor. Computer simulation results are showed that the efficient tracking system for the mobile robot is designed properly.

• Journal of Drive and Control
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• v.13 no.3
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• pp.15-23
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• 2016

The direct-drive servo valve(DDV) is a kind of one-stage valve because the main spool valve is directly driven by the dc motor. Since the DDV structure is simple, it is less expensive, more reliable, and offers a reduced internal leakage and a reduced sensitivity to fluid contamination. The control system of the DDV is highly nonlinear due to a current limiter, a voltage limiter, and the flow-force effect on the spool motion. The shape of the step response of the DDV-control system varies considerably according to the magnitudes of the step input and the load pressure. The system-design requirements mean that the overshoots should be less than 20%, and the errors at 0.02s should be less than 2%, regardless of the reference-step input sizes of 1V and 5V and the load-pressure magnitudes of 0MPa and 20.7MPa. To satisfy the system-design requirements, the PID-controller parameters of $K_c$, $T_i$ and $T_d$, and the derivative-feedback gain of $K_{der}$ are designed using the root locus and manual tuning.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.1-4
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• 1987

A cotroller is designed and implemented for a 4-axis SCARA type assembly robot. The controller is developed for velocity control and precise position control of the AC servo motor and a robot language SNUL-87 is designed using c-language , which is oriented towards an intelligent robot system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.951-954
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• 2005

This paper presents a study on the accuracy position Controller design for the Composite Smoke Bomb Rotational driving system using a BLDC servo motor. Function of Smoke Bomb is blind in the enermy's sight so that need to high response. The BLDC servo motor controller was designed with DSP(TMS320VC33), IGBT(Insulated Gate Bipolar. Transistor), IGBT gate driver and CPLD(EPM7128). This paper implements those control with vector control and MIN-MAX PWM. Vector control requires information about rotor positions, a resolver should be used to achieve that. The main controller is implemented with a TMS320VC33 high performance floating-point DSP(Digital Signal Process) and PWM Generator is embodied using EPM7128.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.3
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• pp.139-146
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• 1998

In this paper, we proposed the hybrid intelligent control method for fast response time and precise speed control of the AC Servo system. The proposed system first used the fuzzy-neural network control methods for fast response time and when the error reaches the preset value, used the PLL control method. In order to verify the advantage of he proposed method, the system is implemented. The results of the simulation and the experiment of speed control to use the 3-phase induction motor as a plant, we verified excellency of the proposed control method to compare with the conventional fuzzy-neural network control method.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.282-285
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• 1989

This paper presents a new algorithm for position control of the BALL-HOOP system driven by th D.C. servo motor-through the micro computer simulation. The Stale Feed back + PID control algorithm is proposed. This algorithm performs that the settling time is faster and overshoot is decreased more remarkably than the PID and the State Feedback algorithm alone. In this simulation the difference equations are used to calculate the output of the control system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.52-57
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• 2007

This paper presents the design of intelligent moving machine control system using a real time speech recognition. The proposed moving machine control system is composed of four separated module, which are main control module, speech recognition module, servo motor driving module and sensor module. In main control module with microprocessor(80C196KC), one part of the artificial intelligences, fuzzy logic, was applied to the proposed intelligent control system. In order to improve the non-linear characteristic which depend on an user's weight and variable environment, encoder attached to the servo motors was used for feedback control. The proposed system is tested using 9 words lot control of the mobile robot, and the performance of a mobile robot using voice and joystick command is also evaluated.