This paper deals with the design problem of robust stabilization and non-fragile controller for discrete-time singular systems with parameter uncertainties and time-varying delays in state and input by delay-dependent Linear Matrix Inequality (LMI) approach. A new delay-dependent bounded real lemma for singular systems with time-varying delays is derived. Robust stabilization and robust non-fragile state feedback control laws are proposed, which guarantees that the resultant closed-loop system is regular, causal and stable in spite of time-varying delays, parameter uncertainties, and controller gain variations. A numerical example is given to show the validity of the design method.

Recently it has been shown in the literature that a biquadratic transformation can be used to deal with the pathological cases arising in the bilinear transformation. This paper concerns the computational aspect of the biquadratic transformation. Two efficient algorithms are presented to compute the transformation matrix.

In this paper, control of an omni-directional mobile robot is presented. Relying on encoder measurements to define the azimuth angle yields the dead-reckoned situation which the robot fails in localization. The azimuth angle error due to dead-reckoning is compensated and corrected by the magnetic compass sensor. Noise from the magnetic compass sensor has been filtered out. Kinematics and dynamics of the omni-directional mobile robot are derived based on the global coordinates and used for simulation studies. Experimental studies are also conducted to show the correction by the magnetic compass sensor.

When the visually impaired walks inside a building like corridor, a GPS cannot be useful for the walker in estimating his or her position unlike the case of outdoor space. This paper presents two novel methods to measure the walking distance using a low cost camera worn on the chest of the visually impaired. In the first method we analyze the periodic variation of image focusing values. Walking steps are counted by checking the period for the rough measure of the walking distance. The second method counts the step number by monitoring fixtures on the ceiling, which have a certain interval. Lamps on the ceiling appeared on the video are monitored in this paper. The T-S fuzzy theory is used to detect lamps, and the walking steps are estimated by the positional variation of the lamp due to the gait of the walker. The two methods are tested in real experiment, and the results are compared.

In this paper, an embedded Kalman filter for a time-delayed controller is designed on an FPGA to estimate accelerations of the robot arm. When the time-delayed controller is used as a controller, the inertia estimation along with accelerations is needed to form the control law. Although the time-delayed controller is known to be robust to cancel out uncertainties in the nonlinear systems, performances are very much dependent upon estimating the acceleration term ${\ddot{q}}(t-{\lambda})$ along with inertia estimation ${\hat{D}}(t-{\lambda})$. Estimating accelerations using the finite difference method is quite simple, but the accuracy of estimation is poor specially when the robot moves slowly. To estimate accelerations more accurately, various filters such as the least square fit filter and the Kalman filter are introduced and implemented on an FPGA chip. Experimental studies of following the desired trajectory are conducted to show the performance of the controller. Performances of different filters are investigated experimentally and compared.

In walking guide robot, a guide vehicle detects an obstacle distribution in the walking space using range sensors, and generates a 3D grid map to map the obstacle information and the tactile display. And the obstacle information is transferred to a blind pedestrian using tactile feedback. Based on the obstacle information a user plans a walking route and controls the guide vehicle. The algorithm for 3D detection of an obstacle distribution and the method of mapping the generated obstacle map and the tactile display device are proposed in this paper. The experiment for the 3D detection of an obstacle distribution using ultrasonic sensors is performed and estimated. The experimental system consisted of ultrasonic sensors and control system. In the experiment, the detection of fixed obstacles on the ground, the moving obstacle, and the detection of down-step are performed. The performance for the 3D detection of an obstacle distribution and space mapping is verified through the experiment.

In this study, we would be developed the fuzzy controlled PGO that controlled the flexion and the extension of each PGO's hip joint using the bio-signal and FSR sensor. The PGO driving system is to couple the right and left sides of the orthosis by specially designed hip joints and pelvic section. This driving system consists of the orthosis, sensor, control system. An air supply system of muscle is composed of an air compressor, 2-way solenoid valve (MAC, USA), accumulator, pressure sensor. Role of this system provide air muscle with the compressed air at hip joint constantly. According to output signal of EMG sensor and foot sensor, air muscles and assists the flexion of hip joint during PGO gait. As a results, the maximum hip flexion angles of RGO's gait and PGO's gait were about $16^{\circ}\;and\;57^{\circ}$ respectively. The maximum angle of flexion/extention in hip joint of the patients during RGO's gait are smaller than normal gait, because of the step length of them shoes a little bit. But maximum angle of flexion/extention in hip joint of the patients during PGO's gait are larger than normal gait.

A new wire detection algorithm for power line inspection by a mobile robot has been proposed in this paper. There have been a lot of studies in order to support the high-quality electric power. For the high-quality power supply, it is necessary to investigate the power lines and insulators before the lines or insulators were disconnected or damaged. Although Korea Electric power Corp. has made many efforts for the quality improvement, it is not enough to inspect all the power lines by human inspectors. According to this problem, it is decided to replace the human operators by the power line inspection robot. When the robots are used for the inspection, there could be several advantages, for example, the working efficiency and the prevention of accident. And also the shortage of human power for dangerous jobs can be resolved. In this paper, as a part of the development of power line inspection robot, DICRO, the sensor fusion and fuzzy control algorithms are developed to detect the wire and slope of the wire. The effectiveness of the proposed algorithms is proved by the real experiments with DICRO which is under development so far.

This paper proposes command signal generating method for a wearable robot using the force as the input signal. The basic concept of this system pursues the combination of the natural and sophisticated intelligence of human with the powerful motion capability of the robot. We define a task for the command signal generation to operate with the human body simultaneously, paying attention to comfort and ease of wear. In this study, we suggest a basic exoskeleton experimental system to evaluate a HRI(Human Robot Interface), selecting interfaces of arm braces on both wrists and a weight harness on the torso to connect the robot and human. We develop the HRI to provide a command for the robot motion. It connects between the human and the robot with the multi-axis load-cell, and it measures the relative force between the human and the robot. The control system calculates the trajectory of end-effector using this force signal. In this paper, we verify the performance of proposed system through the motion of elbow E/F(Extension/Flexion), the shoulder E/F and the shoulder Ab/Ad (Abduction/Adduction).

The common requirements of rough terrain mobile robots are long-term operation and high mobility in rough terrain to perform difficult tasks. In rough terrain, excessive wheel slip could cause an increase in the amount of dissipated energy at the contact point between the wheel and ground or, even more seriously, the robot could lose all mobility and become trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The proposed traction algorithm is analogous to the stick-slip friction mechanism. The algorithm estimates the slippage of wheels by angular acceleration change, and controls the increase or decrease state of torque applied to wheels Simulations are performed to validate the algorithm. The proposed traction control algorithm yielded a 65.4% reduction of total slip distance and 70.6% reduction of power consumption compared with the standard velocity control method.

In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

Urban Search and Rescue (USAR) involves locating, rescuing (extricating), and medically stabilizing victims trapped in confined spaces. In this paper we state the current approach to USAR, address the limitations and discuss the way for moving in rugged topography. To achieve objectives such as surveillance, reconnaissance, and rescue, it is necessary to develop a driving mechanism that can handle rugged geographical features. We propose a new type of driving mechanism for a rescue robot that has a variable shape single-track. By using a variety shapes, it can get the gain of steering and rotating and the ability to overcome stairs. In this paper, we analyzed the design parameters for making variable transform shapes and determined the specifications of the robot to enhance adaptability to stairs.

The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.

This paper proposes a way of expanding the use area of localization technique by using a beacon. In other words, we have developed the auto-calibration algorithm that recognizes the location of this beacon by attaching the beacon on an arbitrary position and by using the information of existing beacon under this situation. By doing so, the moving robot can overcome the limitation that the localization of moving robot is only possible within the area that has installed the existing beacon since the beacon cannot be installed on the accurate location when passing through a danger zone or an unknown zone. Accordingly, the moving robot can slowly move to the unknown zone according to this auto-calibration algorithm and can recognize its own location at a later time in a safe zone. The localization technique is essentially needed in using a moving robot and it is necessary to guarantee certain degree of reliability. Generally, moving robots are designed in a way to work well under the situation that the surroundings is well arranged and the localization techniques of using camera, laser and beacon are well developed. However due to the characteristics of sensor, there may be the cases that the place is dark, interfering radio waves, and/or difficult to install a beacon. The effectiveness of the method proposed in this paper has been proved through an experiment in this paper.

This paper proposes an effective SLAM based on redundant extended Kalman filter for robot navigation in an irregular surface to enhance the accuracy of robot's pose. To establish an accurate model of a caterpillar type robot is very difficult due to the mechanical complexity of the system which results in highly nonlinear behavior. In addition, for robot navigation on an irregular surface, its control suffers from the uncertain pose of the robot heading closely related to the condition of the floor. We show how this problem can be overcome by the proposed approach based on redundant extended Kalman filter through some computer simulation results.

We propose a template matching method for component inspection of SMD assembly system. To discriminate wrong assembled components, the input image of component is matched with its standard image by template matching algorithm. For a fast inspection system, the calculation time of matching algorithm should be reduced. Since the standard images of all components located in a PCB are stored in computer, it is desirable to reduce the memory size of standard image. We apply the discrete wavelet transformation to reduce the image size as well as the calculation time. Only 7% memory of the BMP image is used to discriminate goodness or badness of components assembly. Comparative results are presented to verify the usefulness of the proposed method.

Traction and braking of trains are due to the rolling contact of the wheel on the rail, and the rolling contact is fundamental to an understanding of the behavior of the railroad system. The way in which the forces are transmitted in the rolling contact is complex and highly nonlinear. This paper describes a rolling contact theory, a creepage model between wheel and rail, and a dynamic model of the tilting train Hanvit-200. The validity of the model is verified through simulation study using Simulink.

Modem version of supersonic jet fighter aircraft must have been guaranteed appropriate controllability and stability in HAoA(High Angle of Attack). The HAoA flight control law have two parts, one is control law of departure prevention and the other is control law of departure recovery support. The control laws of departure prevention for advanced jet trainer consist of HAoA limiter, roll command limiter and rudder fader. The control laws of departure recovery support are consist of yaw-rate limiter and MPO(Manual Pitch Override) mode. The guideline of pitch rocking using MPO mode is simple, but operating skill of pitch rocking is very difficult by the pilot with inexperience of departure situation. Therefore, automatic deep stall recovery system is necessary. The system called the "Automatic Pitch Rocker System" or APRS, provided a pilot initiated automatic maneuver capable of an aircraft recoveries in situations of deep stall, speed and altitude. This paper addresses the design and validation for APRS to recovery of an deep stall without manual pitch rocking by the pilot. Also, this system is designed to recovery of speed, attitude and altitude after deep stall recovery using ATCS (Automatic Thrust Control System) and autopilot. Finally, this system is verified by real-time pilot evaluation using HQS (Handling Quality Simulator).