In this paper, the attitude of a quadrotor system is controlled by a time-delayed control method which uses the previous information to cancel out uncertainties in the system. Although the linear controller works for the attitude control, the robust performance against disturbance is relatively poor. Therefore, a time-delayed controller as a robust controller is used. Experimental studies are conducted to validate the performance by the time-delayed control method. The performances of both a linear controller and a time-delayed controller are compared.

This paper presents the effect of a reflective force computed from a first-order-hold method on the stability of a haptic system. A haptic system is composed of a haptic device with a mass and a damper, a virtual spring, a sampler and a sample-and-hold. The boundary condition of the maximum virtual stiffness is analytically derived by using the Routh-Hurwitz criterion and the condition shows that the maximum virtual stiffness is proportional to the square root of the mass and the damper of a haptic device and also is inversely proportional to the sampling time to the power of three over two. The effectiveness of the derived condition is evaluated by the simulation. When the reflective forces are computed by using the first-order-hold method, the maximum available stiffness to guarantee the stability is increased several hundred times as large as when the zero-order-hold method is applied.

Magnetic levitation systems using the attraction force of electromagnets have many constraints according to the variation of air gap and the nonlinearity of electromagnetic force and inductances. As a result of these constraints, the nonlinear control of a magnetic levitation system has been improved by the latest advanced processors and accurate measurement system which can overcome problems such as many constraints and nonlinearity. This paper concentrates on the modeling of a nonlinear magnetic levitation system and an application of an exponential reaching law based sliding mode controller using the exponential reaching law which is one of the most robust controllers against external unexpected disturbances or parameter fluctuations. Controllability of a magnetic levitation system using the sliding mode control algorithm and robustness against parameter fluctuations have been verified through the experimental results.

In this paper, residual sway control of objects that are moved underwater is investigated. The fuel transfer system in a nuclear power plant transfers the nuclear fuel rods underwater. The research on the dynamics of the loads transferred in different mediums (water and air) and their control methods have not been fully developed yet. The attenuation characteristics of the fuel transfer system have been studied to minimize its residual vibration by considering the effects of hydrodynamic forces acting on the fuel rod. First, a mathematical model is derived for the underwater fuel transfer system, and then experiments have been conducted to study the dynamic behavior of the rod while it travels underwater. Lastly, the residual vibration at the end point is minimized using the input shaping technique.

In this paper, we propose a fault diagnosis method based on Park's Vector Approach using the Euler's theorem. If we interpreted it as Euler's theorem, it is possible to easily find the phase angle difference between the healthy condition and the fault condition. And, we analyzed the variation of the phase angle and performed the diagnostic method of the induction motor using feature vectors that were obtained by using a Fourier transform. The analysis of time and speed variation of the motor was performed and, as a result, we could find more soft variations than rough variations. In particular, the analysis of the distortion through each phase shows that two-turn and four-turn shorted motors are linearly separable. In this experiment, we know that the maximum breakdown threshold value for determining steady-state fault detection is 49.0788. Simulation and experimental results show the more detectable than conventional method.

This paper presents a method of ballistic missile launch point estimation using phase division least squares. The proposed algorithm employs smoothing to enhance estimation accuracy and generates functions of time for total velocity, flight path angle and heading angle, allowing extrapolation to estimate the launch point. Performance of the proposed algorithm is tested in conjunction with the extended Kalman filter and the Kalman filter.

This study provides a method to detect blood vessels shape using image processing techniques with the help of fluoroscopy equipments, providing high precision information about vessels' location and shape of inner path. It will assist for checking and monitoring the position of operating tools during vascular interventional treatment. The blood vessels shapes are gathered with X-ray images when a fluorescent medications are injected into patient's vessel and those images are processed for getting the boundaries of vessels. Then these data are merged with real-time CT-images. These image processing systems and procedures recognize the catheter, though continued computing algorithms are very useful for observer part on the automatic control system.

This paper proposes a statistical regression method for classifying pillars and vehicles in parking area using a single ultrasonic sensor. There are three types of information provided by the ultrasonic sensor: TOF, the peak and the width of a pulse, from which 67 different features are extracted through segmentation and data preprocessing. The classification using the multiple SVM and the multinomial logistic regression are applied to the set of extracted features, and has achieved the accuracy of 85% and 89.67%, respectively, over a set of real-world data. The experimental result proves that the proposed feature extraction and classification scheme is applicable to the object classification using an ultrasonic sensor.

Due to electrical cross-coupling between modulation voltage and photodetector output in a closed-loop fiber optic gyro, deadzone inevitably occurs. In this paper, deadzone error by cross-coupling effect was analyzed and the overcoming method was suggested. Simulation and measurement results show the main reason for deadzone is mainly related to electrical cross-coupling, and it can be effectively reduced by square-wave dithering method.

Soft errors in memory devices that caused by radiation are the main threat from a reliability point of view. This threat can be commonly overcome with the combination of SEC (Single-Error Correction) codes and scrubbing technique. The interleaving architecture can give memory devices the ability of tolerating these soft errors, especially against multiple-bit soft errors. And the interleaving distance plays a key role in building the tolerance against multiple-bit soft errors. This paper proposes a reliability model of an interleaved memory device which suffers from multiple-bit soft errors and are protected by a combination of SEC code and scrubbing. The proposed model shows how the interleaving distance works to improve the reliability and can be used to make a decision in determining optimal scrubbing technique to meet the demands in reliability.

This paper presents a method for developing a TM (Traversability Map) from a DTM (Digital Terrain Model) collected by remote sensors of autonomous mobile robots. Such a map can be used to plan traversable paths and estimate navigation speed quantitatively in real time for robots capable of performing autonomous tasks over rough terrain environments. The proposed method consists of three parts: a DTM partition module which divides the DTM into equally spaced patches, a terrain information module which extracts the slope and roughness of the partitioned patches using the curve fitting and the fractal-based triangular prism method, and a traversability analysis module which assesses traversability incorporating with extracted terrain information and fuzzy inference to construct a TM. The potential of the proposed method is validated via simulation works over a set of fractal DTMs.

In this paper, we present a deployable bio-inspired robot called the Pillbot-light, which utilizes a safe autonomous navigation system. The Pillbot-light is mounted the station robot, and can be operated in a disaster relief operation or military operation. However, the Pilbot-light has a challenge to navigate autonomously because the Pilbot-light cannot be equipped with various sensors. As a result, we propose a new robot system for autonomous navigation that the station robot controls Pillbot-light equipped with vision camera and CPU of high performance. This system detects obstacles based on the edge extraction using vision camera. Also, it cannot only achieve path planning using the hazard cost function, but also localization using the Particle Filter. And this system is verified by simulation and experiment.

High precision machining technology has become one of the most important parts in the development of a precision machine. Such a machine requires high precision positioning as well as high speed on a large workspace. For machining systems having high precision positioning with a long stroke, it is necessary to examine the repeatability of the reference position decision. Though ball-screw driven linear stages equipped with linear scale have high precision feed drivers and a long stroke, they have some limitations for reference position decisions if they have not been equipped with an accurate home sensor. This study is performed to experimentally examine the repeatability for home position decision of a photo micro sensor as a home switch of a ball-screw driven linear stage by using a capacitance probe.

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

LEON3 is a 32-bit synthesizable processor based on the SPARC V8. It can be connected to AMBA 2.0 bus and has a 7- stage pipeline, IEEE-754 FPU and 256[KB] cache. It can be easily implemented using FPGA and used for a SoC design. DSU which comes with LEON3 can be used to control and monitor the operation of LEON3. And DSU makes it easy to set a debugging environment for the development of both hardware and software for an embedded systems based on LEON3. This paper presents the summary of the debugging tool for LEON3 based embedded systems. The debugging tool can initialize the target hardware, find out how the target hardware is configured, load application code to a specified memory space and run that application code. To provide users a debugging environment, it can set breakpoints and control the operation of LEON3 correspondingly. And function call trace is one of key functions of the debugging tool.