• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.195-200
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• 2008

This paper presents motion control of the Inchworm composed of the piezoelectric actuators and mechanical elements. Piezoelectric actuator shows nonlinear response characteristics including hysteresis due to the ferroelectric characteristics. This paper proposes feedback control scheme to improve the ability of tracking response to complex input signal and suppress the phenomenon of hysteresis using the sliding mode control technique with the integrator. The sliding mode control system has the limit to minimize both the settle time and overshoot. For making up this limit, this paper also suggests input shaping technique suitable to the inchworm control system.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1832-1833
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• 2006

This paper presents a design method of the wavelet neural network(WNN) controller based on a direct adaptive control scheme for the intelligent control of Autonomous Underwater Vehicle(AUV) steering systems. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome nonlinearities and uncertainty. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and original signal of AUV model that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by gradient-descent method. Through computer simulations, we demonstrate the effectiveness of the proposed control method.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2587-2589
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• 1999

In this paper, we propose a new control scheme for a PWM inverter using digital control. Digital control has various advantages in comparison with conventional analogue control. It can achieve high frequency switching of inverter and can be little influenced for temperature variations and aging of devices. This digitally-controlled PWM inverter is implemented using a Digital Signal Processor(DSPTMS320F240). The simulation results are given to verify the DSP based PWM inverter design and implementation.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.215-218
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• 1995

In this paper, a sliding mode controller (SMC) which can be characterized by high accuracy, fast response and robustness is applied to speed control of AC-SERVO motor. The control input is changed to continuous one in the boundary layer to reduce the chattering phenomenon, and the boundary layer converges to zero when the state variables of system reach to steady state values. The integral compensator is added to reduce steady state error and to provide the continuous torque reference. The acceleration which is necessary to get the sliding plane is estimated by an observer. Sliding surface is included in control input to enhance the robustness and transient response without increasing sliding mode controller gain. The proposed controller is implemented by DSP(digital signal processor). The effectiveness of the proposed control scheme for speed controller is shown by the real-time experimental results in the paper.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1065-1070
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• 2003

We present a power control with variable state feedback gain (VFPC) to improve outage convergence rate of distributed constrained power control. The variable state feedback gain includes the information of the desired SIR changes and must be a decreasing sequence for the convergence. The proof of the convergence is given. The proposed algorithm can improve the outage convergence rate and SIR (Signal to Interference Ratio) response at transient as well as at steady state. The simulation results are given to demonstrate the feasibility of the proposed scheme.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.807-811
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• 2003

In this paper, the speed control system of induction motor was proposed using vector control algorithm and space voltage vector PWM method to improve the dynamic performance of Induction motor. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM technique. The high-speed calculation and processing for vector control is carried out by TMS320C31 digital signal processor and IGBT module. The proposed scheme is verified through digital simulations and experiments for 3.7[kw] induction motor and shows good dynamic performance.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.421-424
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• 1990

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.1-7
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• 2005

This paper is proposed the speed and position sensorless control of surface permanent magnet synchronous motor(SPMSM) with adaptive fuzzy and observer. A adaptive fuzzy controller is applied for speed control of SPMSM drive. A adaptive state observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of SPMSM, that employs a d - q rotating reference frame attached to the rotor. A adaptive observer is implemented to compute the speed and position feedback signal. The validity of the proposed sensorless scheme is confirmed by various response characteristics.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1203-1205
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• 2001

In this paper, the speed control system of induction motor was proposed using vector control algorithm and space voltage vector PWM method to improve the dynamic performance of induction motor. The control system is composed of the PDFF controller for speed control and the current controller using space voltage vector PWM technique. The high-speed calculation and processing for vector control is carried out by TMS320C31 digital signal processor and IPM. The proposed scheme is verified through digital simulations and experiments for 3.7(kw) induction motor and shows good dynamic performance.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.