This paper presents the balancing control of a unicycle robot using air power. Since the robot has one wheel to move forward and backward, the balancing control is quite challenging. To control the balancing angle, the accurate angle estimation by a tilt and a gyro sensor is required a priori. A complementary filter is implemented to eliminate the defects of two sensors and to fuse together to estimate an accurate balancing angle. The optimal design of air ducts is found empirically. Experimental studies of the balancing control of a unicycle robot confirm that the robot is well regulated without falling down.

This paper proposes a MPC (Model Predictive Control) method for the torque and flux controls of induction motor. The proposed MPC method selects the optimized voltage vector for the matrix converter control using the predictive modeling equation of the induction motor and cost function. Hence, the reference voltage vector that minimizes the cost function of the torque and flux error within the control period is selected and applied to the actual system. As a result, it is possible to perform the torque and flux control of induction motor using only the MPC controller without a PI (Proportional-Integral) or hysteresis controller. Even though the proposed control algorithm is more complicated and has lots of computations compared with the conventional MPC, it can perform torque ripple reduction by synthesizing voltage vectors of various magnitude. This feature provides the reduction of amount of calculations and the improvement of the control performance through the adjustment of the number of the unit vectors n. The proposed control method is validated through the PSIM simulation.

In this paper, we propose a method by which QP (Quadratic Programming) problems can be solved in realtime so that we can implement the predictive control algorithm on a microcontroller system. Firstly, we derive a solution to QP problems by converting the original QP problems to its equivalent least squares with inequalities. Secondly, we propose a predictive control algorithm that can give good realtime computation performance by utilizing the fact that some parameters needed for solving QP problems can be computed offline. Finally, we illustrate that the proposed method can give good realtime features by running the C-code application constructed using the proposed method on a microncontroller system.

In this paper, an algorithm is suggested to detect an offset angle of the absolute rotor position sensor after the initial assembly of a PMSG. Unlike previous studies in a stationary state, this one is not designed to detect an electrical angle but rather the absolute position of the rotor is detected while operating the generator. Also,a position sensor, current sensors and voltage sensor were used to ensure reliability. This technique completes the detection of the sensor offset in two steps. In the first step, a zero-crossing of the EMF is measured using a voltage sensor to detect the electrical angle offset when the alternator is actuated by the engine. In the second step, a high frequency current is injected along the d-axis on-line during the control of the generation, eventually to obtain the inductance using a DFT (Discrete Fourier Transform), and then to ultimately extract the final electrical angle offset through the comparison of the inductance magnitude. The suggested algorithm was validated with PSIM simulation and, furthermore, was tested with actual experiments on a dynamometer.

Wind turbines are in the limelight in the alternative energy industry. However, they face frequent and various problems during operation. We focused on the supervising of the blades of a wind turbine. In this paper, we present the design of a maintenance robot that takes the size of wind turbine blades into consideration, so the general form of the robot is a square with four wires fixed to its vertices and to the nacelle. After the robot is placed near the nacelle, it moves along the blades. We also designed an attitude control algorithm for the robot to maintain its balance. Our control algorithm for the robot consists of roll and pitch attitude controllers and a height controller. Each controller was designed independently and then superposed together. We used simulations to verify our control algorithm.

A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.

Walking mechanisms are very important for legged robots to ensure their stable locomotion. In this research, Klann-linkage is suggested as a walking mechanism for a water-running robot and is optimized using level average analysis. The structure of the Klann-linkage is introduced first and design variables for the Klann-linkage are identified considering the kinematic task of the walking mechanism. Next, the design problem is formulated as a path generation optimization problem. Specifically, the desired path for the foot-pad is defined and the objective function is defined as the structural error between the desired and the generated paths. A process for solving the optimization problem is suggested utilizing the sensitivity analysis of the design variables. As a result, optimized lengths of Klann-linkage are obtained and the optimum trajectory is obtained. It is found that the optimized trajectory improves the cost function by about 62% from the initial one. It is expected that the results from this research can be used as a good example for designing legged robots.

In this paper, a new steering system for a self-balancing electric scooter is proposed with an intuitive steering command input method, where the steering command is generated from the rider's motion of shifting body to move the center of gravity toward the rotational direction. For the purpose, weight distributions on the rider's feet are measured using force sensors placed beneath the rider's feet, and the difference is applied to a steering control system. Stability of the steering system and resultant radius of gyration is investigated by modeling the steering system in consideration of the rider's motion and centrifugal force. The proposed steering system is applied to experiments, and the results are presented to prove the validity of the proposed method.

In this paper, the real-time detection method of a DDP (Driving Direction Point) is proposed for an unmanned vehicle to safely follow the center of the road. Since the DDP is defined as a center point between two lanes, the lane is first detected using a web camera. For robust detection of the lane, the binary thresholding and the labeling methods are applied to the color camera image as image preprocessing. From the preprocessed image, the lane is detected, taking the intrinsic characteristics of the lane such as width into consideration. If both lanes are detected, the DDP can be directly obtained from the preprocessed image. However, if one lane is detected, the DDP is obtained from the inverse perspective image to guarantee reliability. To verify the proposed method, several experiments to detect the DDPs are carried out using a 4 wheeled vehicle ERP-42 with a web camera.

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

In this study we have developed an anthropomorphic robot hand and arm by using tendon-tubes which can be used for people's everyday life as a robot's dynamic power transmission device. Most previous robot hands or arms had critical problem on dynamic optimization due to heavy weight of power transmission parts which placed on robot's finger area or arm area. In order to resolve this problem we designed light-weighted robot hand and arm by using tendon-tubes which were consisted of many articulations and links just like human's hand and arm. The most prominent property of this robot hand and arm is reduction of the weight of robot's power transmission part. Reduction of weight of robot's power transmission parts will allow us to develop energy saving and past moving robot hands and arms which can be used for artificial arms. As a first step for real development in this study we showed structural design and demonstration of simulation of possibility of a robot hand and arm by tendon-tube. In the future research we are planning to verify practicality of the robot hand and arm by applying sensing and controlling method to a specimen.

Haptic device can be a useful rehabilitation tool in balance training. The proposed system is composed of a body-wear smartphone, Phantom Omni(R) device, and its control PC system. Ten young healthy subjects performed balance tasks with different postures during 30 seconds with their eyes closed. An Android program on the smartphone transferred mediolateral (ML) and anteroposterior (AP) tilt angles to the PC system, which can generate haptic command through haptic device. Statistical data analysis was performed using MATLAB(R). COP (Center of Pressure) related indexes were measured to see reduction in body sway. ANOVA showed that haptic device significantly reduced body sway. Intuitive balance guidance could be generated using an economical and small-sized commercial haptic device, making the system efficient.

A repeat-back jamming signal is an intentionally re-broadcasted GNSS (Global Navigation Satellite System) interference. In this paper, a novel repeat-back jamming detection scheme is proposed. The proposed scheme uses a combined pseudo random noise signal (C-PRN) and is available for a generic GNSS receiver with a single antenna. The C-PRN signal is made by combining several received pseudo random noise signals that had been transmitted from the visible GNSS satellites. Through a Monte-Carlo simulation, the detection probability of a repeat-back jamming signal detected with the proposed scheme is presented.

In this paper, we propose a design for an efficient hybrid LED street lighting management system using standalone solar photovoltaic. The proposed efficient hybrid LED street lighting management system was composed of hybrid power conditioning system, gateways, LED street lights and a monitoring server. The hybrid power conditioning system was designed to charge produced power by solar photovoltaic panels in day time, and supply power to the LED street lights in night time. If there is insufficient power, the system was designed to operate using firm power, because the system utilizes photovoltaic power. A system control algorithm allied to the lighting management system, and experimented by being configured to the functions that are able to perform real-time monitoring and remote control through the lighting management system even when absent. In the result of the efficiency analysis of the hybrid lighting management system proposed in this paper, we were able to increase the energy efficiency compared to existing lighting control systems by reducing power consumption and electricity costs.