This paper presents a new control algorithm for dynamic control of a unicycle robot. The unicycle robot motion consists of a pitch that is controlled by an in-wheel motor and a roll that is controlled by a reaction wheel pendulum. The unicycle robot doesn't have any actuator for a yaw axis control, which makes the derivation of the dynamics relatively simple. The Euler-Lagrange equation is applied to derive the dynamic equations of the unicycle robot to implement the dynamic speed control of the unicycle robot. To achieve the real time speed control of the unicycle robot, the sliding mode control and LQ regulator are utilized to guarantee the stability while maintaining the desired speed tracking performance. In the roll controller, the sigmoid-function based sliding mode controller has been adopted to minimize the chattering by the switching function. The LQR controller has been implemented for the pitch control to drive the unicycle robot to follow the desired velocity trajectory in real time using the state variables of pitch angle, angular velocity, angle and angular velocity of the wheel. The control performance of the two control systems form a single dynamic model has been demonstrated by the real experiments.

High precision machining technology has become one of the 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 a high precision positioning with a long stroke, it is necessary to examine the repeatability of reference position decision. Though ball-screw driven linear stages equipped linear scale have high precision feed drivers and a long stroke, they have some limitations for reference position decision if they have not equipped the accurate home sensor. This study is performed to experimentally examine the repeatability for home position decision of a magnetic sensor as a home switch of ball-screw driven linear stage by using capacitance probe.

This paper proposes a classification method of parallel, vertical parking states and pillars for parking assist system using ultrasonic sensors. Since, in general parking space detection module, the compressed amplitude of ultrasonic data are received, the analysis of them is difficult. To solve these problems, in preprocessing state, symmetric transform and noise removal are performed. In feature extraction process, four features, standard deviation of distance, reconstructed peak, standard deviation of reconstructed signal and sum of width, are proposed. Gaussian fitting model is used to reconstruct saturated peak signal and discriminability of each feature is measured. To find the best combination among these features, multi-class SVM and subset generator are used for more accurate and robust classification. The proposed method shows 92 % classification rate and proves the applicability to parking space detection modules.

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.

This paper proposes the implementation of robust fuzzy controller for designing intelligent wind farm and mitiagating the fluctuation of wind power generator. The existing researches are limited to individual wind turbine with variable speed so that it is necessary to study the multi-agent wind turbine power system. The scopes of these studies include from the arrangements of each power turbine to the control algorithms for the wind farm. For solving these problems, we introduce the composition of intelligent wind farm and use the T-S (Takagi-Sugeno) fuzzy model which is suitable for designing fuzzy controller. The control object in wind farm enables the minimizing the fluctuation of wind power generator. Simulation results for wind fram which is modelled as mathematically are demonstrated to visualize the feasibility of the proposed method.

The ball-shaped mobile robot, so called ballbot has single point contact on ground and low energy consumption in motion because of the reduced friction. In this paper, a new ballbot is presented, which has omnidirectional mobile platform inside of it as a driving system. Thus the ballbat has omnidirectional mobility without nonholonomic constraints. Kinematics and inverse kinematics of the ballbat is derived also in this paper.

With the recent advancement of control method and battery technology, the electric vehicle have been researched to replace the conventional vehicle with electric vehicle with the view point of the environmental concerns and energy conservation. An electric vehicle which is equipped with the independent front steering system and in-wheel motors has advantage in terms of control. For example, the different torque which generated by left and right wheels directly can make yaw moment and the independent steering using outer wheel control is able to reduce the sideslip angle. Using of independent steering and driving system, the 4 wheel electric vehicle can improve a performance better than conventional vehicle. In this paper, we consider the method for improving the cornering performance of independent front steering system and in-wheel motor used electric vehicle with the compensated outer wheel angle and direct yaw moment control. Simulation results show that the method can improve the cornering performance of 4 wheel electric vehicle. We also apply the steering motor failure to steer the vehicle turned by the torque difference without steering. This paper describes an independent front steering and driving, consist of three parts; Vehicle Model, Control Algorithm for independent steering and driving and simulation. First, vehicle model is application of TruckSim software for independent front steering and 4 wheel driving. Second, control algorithm describes the reduced sideslip and direct yaw moment method in view of cornering performance. Last is simulation and verification.

We propose an efficient minimum-time cornering motion planning algorithms for differential-driven wheeled mobile robots with motor control input constraint, under piecewise constant control input sections. First, we established mobile robot's kinematics and dynamics including motors, divided the cornering trajectory for collision-free into one translational section, followed by one rotational section with angular acceleration, and finally the other rotational section with angular deceleration. We constructed an efficient motion planning algorithm satisfying the bang-bang principle. Various simulations and experiments reveal the performance of the proposed algorithm.

In this work, new smart phone based moving target detection is proposed. In order to implement the task, methods of real time image transmission from network camera, motion detecting algorithm and its effective implementation are also addressed. The network camera transfers image data by MJPEG format which contains various information such as data and IP address, and the smart phone separates the image data received through a WiFi module. Later, the image data is converted to a Bitmap image format, and with the help of the embedded OpenCV library on a smart phone and algorithm, it was found that the moving object was identified effectively in terms of real time monitoring and detection.

Different scanning methods can be used to detect targets of interest in an image. In this paper, four scanning methods, generalized raster scanning, radial scanning, corner scanning, and random scanning, are considered for the evaluation of their scanning performances. The scanning performance is defined here as the ratio of the average scanning area required to detect a single target to the whole image area. Analytic expressions for the performance of each scanning method are derived. Computational results are given to illustrate the usage and validity of the expressions for the performance comparison.