• Proceedings of the KIEE Conference
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• summer
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• pp.1037-1039
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• 2004

A typical conventional systems of a linear motion use rack and pinions or ball screws to convert rotary motions from DC servo motors. A linear motor has been used a several field for a MEMS technology and a aircraft carrier. We was studied a transient response of a linear actuator with a damping ratio, spring constant and a pressed power.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.5
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• pp.426-430
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• 2006

This paper deals with a novel utilization method of the predicted current in the high performance PI current controller with a control time delay. The inevitable error of the predicted current in the linear servo drive using a permanent magnet linear synchronous motor is analyzed and a modified cross-coupling decoupling synchronous frame PI current controller is proposed in order to improve the current control response under both the control time delay and the inevitable current prediction error. Simulation and experimental results show that the proposed current controller has an improved current control performance under both the control time delay and the inevitable current prediction error in the servo drive system.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.314-316
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• 2001

This paper present the position control method for the application of permanent magnet linear synchronous motor. Controller is designed as a conventional P-PI controller, but the extra information is used such as velocity and acceleration from motion profiles. The profiles comes from S-Curve which is an optimized point-to-point motion profiles to achieve fast motions with minimum vibration[2]. In this application, the targets of the position control are maximum 10um position error within 10msec after respective ending point of position profiles. The implementation of the controller has been done in full digital way. All the controller is designed on the DSP TMS320VC33 control board. To prove performance of the controller, the experiment was performed with a servo linear motor.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.3
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• pp.97-103
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• 1995

In this paper, for fuzzy control of linear servo system using the moving coil type linear DC motor, we propose a new fuzzy control method using parameter tuning for membership functions. A proposed fuzzy control method tunes parameters of membership function to have an appropriate control input signal for system when error exceeds predefined value and makes an inference using conventional fuzzy control rules when error reduces to a predefined value. To verify usefulness of a proposed fuzzy control method, making simulation and experiment, we compare with characteristics for conventional fuzzy control method.

• Proceedings of the KIEE Conference
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• 1985.07a
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• pp.306-309
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• 1985

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.1
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• pp.26-32
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• 1993

The loads exerted on electro-hydraulic servo system are classified into inertial, viscous, and spring load. The additional load called disturbances is also exerted on system but is generally not modeled. To deal with these kinds of loads, it is necessary to maintain the continuous signal transfer, so we can construct compensator to satisfy control specifications using feedback signal such as displacement, velocity, acceleration and pressure known as state variables. In case of controlling the speed of hydraulic motor, we must keep up robust performance for the various loads and disturbances acted on the system. However, the load flow rate in the valve is characterized by nonlinearity so that traditional theory of linear control could not be expected to give the desired performance. In this paper, it is shown that speed controller of hydraulic motor gives a good command following and disturbance rejection performance by applying sliding mode theory as a way of robust control to the nonlinearity, variation of loads and disturbances.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.175-186
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• 2021

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm forthe controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1387-1392
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• 1990

In this paper, an iterative learning control algorithm for unknown linear discrete systems is proposed by employing a parameter estimator together with an inverse system model. Regardless of initial error and inherent parameter uncertainty, a good tracking control performance is obtained using the proposed learning control algorithm characterized by recursive operations. A sufficient condition for convergency is provided to show the effectiveness of the proposed algorithm. To investigate the performance of the algorithm a series of simulations and experiments were performed for the tracking control of a servo motor.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.738-750
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• 1994

The load-sensing hydraulic system which was developed to improve energy efficiency of conventional hydraulic systems has its own properties. The instability of system responses, linearity of a servo valve, robustness for variation of external load, and dynamic interference between hydraulic motors are such properties which have much to do with control properties of the system. The load-sensing hydraulic system has instability tendancy because the load-sensing mechanism makes a positive feedback loop between the motor part and the pump part. A flow property of the servo valve can be said to be linear because the flow through the valve has nothing to do with a load pressure and the flow is strictly proportional to a valve opening which is adjusted by a valve command signal. The resultant control property can be said to be robust because the steady-state control performance is independent to the load actuated on the motor shaft. In the case when one pump simultaneously drives more than two hydraulic motors, the pump outlet pressure is determined by a hydraulic motor of the largest load pressure among all of the hydraulic motors, and, thus, the other motors are dominated by the largest load pressure. That is, the other motors can be said to be interfered by the motor of the largest load pressure.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.408-421
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• 2015

Because the wheel of V-belt continuously variable transmission (CVT) system driven by permanent magnet synchronous motor (PMSM) has much unknown nonlinear and time-varying characteristics, the better control performance design for the linear control design is a time consuming job. In order to overcome difficulties for design of the linear controllers, a hybrid recurrent Chebyshev neural network (NN) control system is proposed to control for a PMSM servo-driven V-belt CVT system under the occurrence of the lumped nonlinear load disturbances. The hybrid recurrent Chebyshev NN control system consists of an inspector control, a recurrent Chebyshev NN control with adaptive law and a recouped control. Moreover, the online parameters tuning methodology of adaptive law in the recurrent Chebyshev NN can be derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, the optimal learning rate of the parameters based on discrete-type Lyapunov function is derived to achieve fast convergence. The recurrent Chebyshev NN with fast convergence has the online learning ability to respond to the system's nonlinear and time-varying behaviors. Finally, to show the effectiveness of the proposed control scheme, comparative studies are demonstrated by experimental results.