The damping ratio ${\xi}$ of the unit-step response of a second-order discrete system is a function of only the location of the closed-loop poles and is not directly related to the location of the system zero. However, the peak overshoot of the response is the function of both the damping ratio ${\xi}$ and an angle ${\alpha}$, which is the phasor angle of the damped sinusoidal response and is determined by the relative location of the zero with respect to the closed-loop poles. Therefore, if the zero and the open-loop poles are relatively adjusted, through pole-zero cancellation, to maintain the desired (or designed) closed-loop poles, the damping ratio ${\xi}$ will also be maintained, while the angle ${\alpha}$ changes. Accordingly, when the closed-loop system poles are fixed, the peak overshoot is considered as a function of the angle ${\alpha}$ or the system zero location. In this paper the effects of the relative location of the zero on the system performance of a second-order discrete system is studied, and a design method of digital compensator which achieves a minimum peak overshoot while maintaining the desired system mode and the damping ratio of the unit step response is presented.

In this paper, a suspension control of a magnetic levitation(MagLev) system with flexible rail is designed and presented. The numerical modelling for the electromagnetic system to be controlled as a target plant is carried out. And dome kinds of the hardware system including CPU board, AD board, DA board, sensors, and switching power amplifier are described. Using the derived model, the stabilizing controllers, such as PID and $H_{\infty}$ controller, for the MagLev system are designed using the MATLAB toolbox. The designed controllers are validated by some experimental results as well as numerical simulations. So it is shown that $H_{\infty}$ controller can give the better performance for the plant with flexible modes than PID controller.

In this paper, the robust non-fragile guaranteed cost control problem is studied for a class of linear large-scale systems with uncertainties and a given quadratic cost functions. The uncertainty in the system is assumed to be norm-bounded and time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design a state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible uncertainties and controller gain variations. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost controllers is given in terms of the feasible solutions to a certain LMI. A numerical example is given to illustrate the proposed method.

In this paper, the robust adaptive controller design scheme is studied for nonlinear systems in the presence of bounded disturbances A new robust adaptive controller is designed using high-order neural networks, which avoids the singularity problem in adaptive nonlinear control. The stability of the resulting adaptive system with the proposed adaptive controller si guaranteed by suitably choosing the design parameters and initial conditions. I addition, the proposed adaptive controller provides improved transient performance and fast on-line adaptation. The ability and effectiveness of the proposed adaptive control scheme is shown trough simulations of a simple nonlinear system.

n industrial computer vision systems, the image quality is dependent on the parameters such as light source, illumination method, optics, and surface properties. Most of them are related with the lighting system, which is designed in heuristic based on the designer's experimental knowledge. In this paper, a design code by which the optimal lighting method and light source for computer vision systems can be found are suggested based on experimental results. The design coed is applied to the design of the lighting system for the transistor marking inspection system, and the overall performance of the machine vision system with the lighting system show the effectiveness of the proposed design code.

The Hemodialysis system is the device for the patients who have suffered from end stage renal failure as the kidney which removes the waste products in a human body. The existing hemodialysis is based on a 8-bit micro-controller and it is not a touch-screen type but a manual type. This paper is focused on hemodialysis system based on high control and expension embedded system. The whole system consists of main control unit and sub control unit(dialysis control unit, blood control unit, monitoring control unit, networking unit). The dialysis control unit, blood control unit, monitoring control unit are processed by 3 microcontrollers and network unit is for monitoring a renal failure patient's condition. For the evaluation of the system performance, the saline was pured into blood unit and then water removal rate, conductivity and temperature of hemodialysis liquid were measured 10 times in an each state suing the UF pump in the fluid unit varing the quantity of saline to 1000cc, 2000cc, 3000cc and 4000cc. As a result, the rates of water removal are 98.6% in condition of 000cc saline, 96.9% in 2000cc, 98.9% in 3000cc and 98.3% in 4000cc. The conductivities of hemodialysis liquid are 99.6% in the first to third condition and 99.7% in the forth condition. The temperatures of hemodialysis liquid are 99.8% in the first to third condition and 99.6% in th forth condition.

This paper describes a technique for human sensibility evaluation using EEGs of 4 emotions. The proposed method uses the linear predictor coefficients as EEG feature parameters and a neural network as sensibility pattern classifier. For subject independent system, multiple templates are stored and the most similar template can be selected. EEG signals corresponding to 4 emotions such as relaxation, joy, sadness and anger are collected from 5 armature performers. The states of relaxation and joy are considered as positive sensibility and those of sadness and anger as negative. The classification performance suing the proposed method is about 72.6%. This may be promising performance in the human sensibility evaluation.