In this paper, we propose a fault diagnosis scheme tor induction motor by adopting a hierarchical classifier consisting of k-Nearest Neighbors(k-NN) and Support Vector Machine(SVM). First, some motor conditions are classified by a simple k-NN classifier in advance. And then, more complicated classes are distinguished by SVM. To obtain the normal and fault data, we established an experimental unit with induction motor system and data acquisition module. Feature extraction is performed by Principal Component Analysis(PCA). To show its effectiveness, the proposed fault diagnostic system has been intensively tested with various data acquired under the different electrical and mechanical faults with varying load.

The OBC(on-board computer) of a satellite which plays a role of the controller for the satellite should be equipped with preventive measures against transient errors caused by SEU(single event upset). Since memory devices are pretty much susceptible to these transient errors, it is essential to protect memory devices against SFU. A common method exploits an error detection and correction code and additional memory devices, combined with periodic memory scrubbing. This paper proposes an effective memory scrubbing scheme for the OBC of STSAT-2. The memory system of the OBC is briefly mentioned and the reliability of the information stored in the memory system is analyzed. The result of the reliability analysis shows that there exist optimal scrubbing periods achieving the maximum reliability for allowed overall scrubbing overhead and they are dependent on the significance of the information stored. These optimal scrubbing periods from a reliability point of view are derived analytically.

In this paper, a performance comparison between traditional TPN (true proportional navigation) guidance law and PPN(pure proportional navigation) guidance law is made, based on a short range surface-to-air missile simulation program. This simulation program has a nonlinear aerodynamic missile model, a roll stabilized autopilot, a nonlinear radar model, and a target model, According to the simulation results, the PPN guidance law has better performances than TPN guidance law under the condition of evasive target.

This paper presents a power quality assessment model based on the Analytic hierarchy process. This model can assess unified power quality index which provide an overall performance of the distribution system. To obtain the unified power quality index, we propose the use of the AHP model which has three states: [Ideal]-[Actual]-[Worst]. The proposed method is especially useful and effective for planning. We have applied the proposed method to an actual relatively large system, and verified the usefulness.

In this paper, motion analysis algorithm is presented for home surveillance of the aged who lives alone. For the first step, we acquire images from a camera. To enhance the image, we use median filtering and binarize it to reduce processing time. And then morphological operations are performed to remove small blobs and small holes. At the forth step, blobs are analysed to extracts tor foreground region. Then, motions are predicted from these images by using optical tlow technique, and the predicted motion data are refined by comparing our cardboard models so as to judge behavior pattern.

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

This thesis presents a kind of active noise control(ANC) algorithm for reducing noise due to engine inside a car. The proposed control algorithm is, by using WP(Wavelet Packet), a one improving the instability due to delay of noise transmission and the lack of response ability for the rapid change of noise, which are defects of the existing FXLMS(Filtered-X Least Mean Square) algorithm. The chief character of this system is a thing that faster operation than the FXLMS is implemented by inserting WP in the secondary path. In other words, WP implements parallel operation. Then, the weights of filter in the adaptive algorithm will be updated faster. In addition, because WP have so excellent a resolution, they can process very minute noise. The efficiency of this control algorithm will be demonstrated in the matlab simulation and in the actual experiments by using a Labview program and a car.

There are few representative humanoid robots including Japanese ASIMO from Honda and HUBO from KAIST. We cannot consider ASIMO and HUBO the perfect humanoid robots, however. The basic principles when developing humanoid robot is to make them to work in a similar way as human's movement of arm. In this paper, we proposed method of designing humanoid robotic arms based on the morphological.eurological analysis of human's arm tor robot's arm to work in a similar way as human's ann, and we also implemented arm movement control system to humanoids robot by using SERCOS communication.

The objective of this research is to optimize the designing parameters of the parallel manipulator with large orientation workspace at the boundary position of the constant orientation workspace (COW). The method uses a simple genetic algorithm(SGA) while considering three different kinematic performance indices: COW and the global conditioning index(GCI) to evaluate the mechanism's dexterity for translational motion of an end-effector, and orientation workspace of two angle of Euler angles to obtain the large rotation angle of an end-effector at the boundary position of COW. Total fifteen cases divided according to the combination of the sphere radius of COW and rotation angle of orientation workspace are studied, and to decide the best model in the total optimized cases, the fuzzy inference system is used for each case's results. An optimized model is selected as a best model, which shows better kinematic performances compared to the basis of the pre-existing model.

Environmental information (temperature, humidity, vibration, $CO_2$, gas leakage, etc.) of building is an essential item to manage and monitor a building. For intelligent building, it is necessary to get temperature and illumination information to save energy and crack information to prevent structural problems. Moreover, temperature and gas leakage information to alarm a tire precaution, or humidity information to maintain comfortable environment. However, there have not been many researches on systems for gathering environmental information and building maintenance due to high costs. In this paper, wireless sensor network technology is applied to collecting building environmental information. Wireless sensor network is one of the latest issues and has low-power consumption, low-cost, self-configuration features.

This paper deals with LQR controller design method tor system having complex poles. The proposed method is capable of systematically calculating weighting matrices based on the pole's moving-range and the relational equation between closed-loop pole(s) and weighting matrices. The method moves complex poles to complex poles or two distinct real poles. This will provide much-needed functionality to apply LQR controller. The example shows the feasibility of the proposed method.

In this paper, we propose a delayed feedback guaranteed cost controller design method for linear time-delay systems with norm-bounded parameter uncertainties and nonlinear perturbations. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, an LMI optimization problem is formulated to design a controller such that the closed-loop cost function value is not more than a specified upper bound for all admissible system uncertainties and nonlinear perturbations. Numerical example show the effectiveness of the proposed method.

This paper presents a new method on controller design of brushless dc motors. In such drives the current ripples are generated by motor inductance in stator windings and the back EMF. To suppress the current ripples the current controller is generally used. To minimize the size and the cost of the drives it is desirable to control motors without the current controller and the current sensing circuits. To estimate the motor CUlTent it is modeled by a neural network that is contigured as an output-error dynamic system. The identified model is essentially a one step ahead prediction structure in which past inputs and outputs are used to calculate the current output. Using the model, a state feedback controller to compensate the effects of disturbance has been designed. The controller is implemented by a 16-bit microprocessor and the effectiveness of the proposed control method is verified through experiments.

Recently, many ECUs(Electronic Control Units) have been used to enhance the vehicle safety, which leads to a distributed real-time control system. The distributed real-time control system requires to reduce the network delay for dependable real-time performance. There are two different paradigms by which a network protocol operates: event-triggered and time-triggered. This paper focuses on implementation of a time-triggered protocol. i.e. TTP/C(Time-Triggered Protocol/class C). This paper presents a design method of TTP control network and performance evaluation of distributed real-time control system using TTP protocol.

In the conventional AOA(angle-of-arrival) positioning utilizing reverse-link wireless channel, each sensor should be equipped with an array antenna to measure the incident angle of signal transmitting from a tag. To perform the complicated signal processing for angle measurements, sensor size and its power consumption will be large. In some applications like mobile robot location, there exists no strict restriction in tag size or in power consumption. Rather, it is desirable that the sensor would be as small as possible. This paper presents a new AOA positioning method utilizing forward-link channel. Under the assumption that the mobile robot is operating on the flat surface, the measurement model for FLAOA(tiJrward-link AOA) is derived first. Two kinds of position estimation algorithms using FLAOA measurements are proposed; Gauss-Newton method and closed-fonn solution method. With the proposed methods, we can ohtain the attitude of robot as well as its position. Positioning performance of proposed methods is compared by computer simulation. Simulation results show that the closed-form solution method using FLAOA measurements is suitable for indoor robot positioning.