• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.30-35
• /
• 1990

Learning control of a robot manipulator is proposed using the backpropagation neural network. The learning controller is composed of both a linear feedback controller and a neural network-based feedforward controller. The stability analysis of the learning controller is presented. Three energy functions are selected in teaching the neural network controller : 1/2.SIGMA.vertical bar torque error vertical bar $^{2}$, 1/2.SIGMA..alpha. vertical bar position error vertical bar $^{2}$ + .betha. vertical bar velocity error vertical bar $^{2}$ + .gamma. vertical bar acceleration error vertical bar $^{2}$ and learning methods are presented. Simulation results show that the learning controller which is learned to minimize the third energy function performs better than the others in tracking problems. Some properties of the learning controller are discussed with simulation results.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.358-363
• /
• 1987

It is widely noted that pressure feedback systems have been devised to damp the fluid resonance effectively in precision speed control-for large inertia system. A compensation technique preserving the natural output disturbance discrimination characteristics at lower frequencies is proposed The load pressure across positive displacement acceleration. The technique involves feeding back load differential pressure, sensed by pressure transducers, though a simple analog compensatory circuit (high pass filter). The effectiveness of the damping is determined by the filter time donstant and loop gain. Nonlinear total hydraulic simulation results verify the possibility of linear model predictions of extending the closed loop bandwidth beyond the uncompensated frequency.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.881-885
• /
• 2008

To calculate the attitude in ARS(Attitude Reference System) using 3 gyros and 3 accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error. Kalman filter is most popular method to integrate those two sensor outputs. In this paper, new Kalman filtering method is proposed for roll and pitch attitude estimation. New states are defined to make linear equation and algorithm for changing Kalman filter parameters is proposed to ignore disturbances of acceleration. This algorithm can be easily applied to low cost ARS.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.3
• /
• pp.386-393
• /
• 2008

A position control method for interpolating aspherical grinding and polishing tool path was reviewed and experimented in a nano precision machine. The position-base algorithm was reformed from the time-base algorithm, proposed in the previous study. The characteristics of the algorithm were in the velocity control loop with position feedback. The aspherical surface was divided by an interval at which each velocity and acceleration were calculated. The theoretical velocity was corrected by position error during processing. In the experiment, a machine was constructed and nano-scale linear encoders were installed at each axis. Relation between process parameters and the variation of position error was monitored and discussed. The best result from optimized parameters showed that the accuracy was 150nm and improved from the previous report.

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.287-289
• /
• 1995

In this paper, We applied the $\mu$-stepping method on the Phase Excitation Sequence of Hybrid type LPM. Linear Pulse Motor can opeate in an open loop control as an effective positioning actuator. PWM driver was used for low power loss and automatically adjusted voltage at rate current. Finally we find that through the position-velocity for timing Triangular and Trapezoidal Profile are very affected by velocity and acceleration parameter.

• Journal of computational fluids engineering
• /
• v.3 no.2
• /
• pp.65-72
• /
• 1998

From the Boltzmann equation with BGK approximation, a gas-kinetic BGK scheme is developed and methods for its efficient calculation, using the convergence acceleration techniques, are presented in a framework of an implicit time integration. The characteristics of the original gas-kinetic BGK scheme are improved in order for the accurate calculation of viscous and heat convection problems by considering Osher's linear subpath solutions and Prandtl number correction. Present scheme applied to various numerical tests reveals a high level of accuracy and robustness and shows advantages over flux vector splittings and Riemann solver approaches from Euler equations.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.8
• /
• pp.1281-1286
• /
• 2003

A line search algorithm to increase a convergence in Newton's method is developed and applied to nonlinear finite element analysis. The algorithm is based on the slack line search theory which is an efficient algorithm to determine initial acceleration coefficient, variable backtracking algorithm proposed by some researchers, and convergence criterion based on residual norm. Also, it is capable of avoiding exceptional diverging conditions. Developed program is tested in metal forming simulation such as forging and ring rolling. Numerical result shows the validity of the algorithm for a highly nonlinear system .

• Proceedings of the KIPE Conference
• /
• 1998.10a
• /
• pp.325-329
• /
• 1998

This paper describes the controller for the improving speed control of the AC servo motor. The microprocessor provides an output to the difference in command. the servo system improves the characteristics of speed control. When the motor is running at the same speed as set by the reference signal, the speed encoder also provides a signal of the same frequency. Thus, the microprocessor controlled digital techniques enable to realize the flexible performance and control which was possible with time constant of linear acceleration/deceleration. We can know that optimal speed of machining center is 75msec in 30000mm/min and actually, 75msec is using on machining center. Finally experimental results prove excellent performance of this control system. This can be reduced error with more exact measure of actual speed. The system can be adaptable to CNC machine.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.414-419
• /
• 1994

In recent years, there has been an increasing intest in control of active automotive suspension systems with a goal of improving the ride comfort and safety. Many approaches for these purposes have used linearized models of the suspension's dynamics, allowing the use of linear control theory. However, the linearized model does not well descriibe the actual system behavior which is inherently nonlinear. The object of this study is to develop a neuro controlled active suspension for the ride quality improvement. After obtaining active control law using optimal control theory, we use the artificial neural network to train the neuro controller to learn the relation of road input and control force. Form the numerical results, we found that back propagation learning does show good pattern matching and vertical acceleration of the driver's seat and sprung mass.

• Journal of the Korean Society for Precision Engineering
• /
• v.25 no.4
• /
• pp.86-92
• /
• 2008

This paper is to investigate the behavior of linear static structure stress, the fatigue and experimental shock fracture far engine base in the Auxiliary Power Unit to resolve its restricted electrical power problem. The shock fracture test was experimentally made under MIL standard criteria. The numerical results by finite element method had a good agreement with those from the shock test. The design data of predicting the fracture at the initial crack and the damage behavior of structure with shock and vibration load in the battle field can be obtained from shock test. In the functional shock test, the crack at the side parts of the engine base was found at peak acceleration of 40g.