This paper presents a new approach to analyze the stability of dynamic competitive markets within the framework of supervisory control of discrete event systems. A competitive market is representative of free market economy where it is well known that an invisible hand (also referred to as Walrasian auctioneer) always achieves an equilibrium of demand and supply. Upon the framework of supervisory control theory, this paper shows that Walrasian auctioneer is a stabilizing supervisor for a convergent competitive market, however a non-convergent competitive market (e.g. a free market under economic bubble and depression) controlled by Walrasian auctioneer may not be stable.

If an internal combustion engine is operated by consolidated control, the minimum fuel consumption is achieved and the demanded objectives are satisfied. For this, it is necessary that the engine is operated on the ideal operating line which satisfies minimum fuel consumption. In this context of view, there are many tries to achieve given object. However, the parameters in the internal combustion engines are variable and depend on the operating points. Therefore, it is necessary to cope with the uncertainties such that the optimal operating may be possible. From this point of view, this paper gives a controller design method and a robust stability condition for engine torque control which satisfies the given control performance and robust stability in the presence of physical parameter perturbation. Exactly, in this paper, we consider the robust stability problem of this 2DOF servosystem with nonlinear type uncertainty in the engine system, and a robust stability condition for the servosystem is shown. This result guarantees that if the plant uncertainty is in the permissible set defined by the given condition, then a gain tuning can be carried out to suppress the influence of the plant uncertainties.

In this paper, an adaptive sliding-mode formation control and collision avoidance are proposed for electrically driven nonholonomic mobile robots with model uncertainties and external disturbances. A sliding surface based on the leader-follower approach is developed to achieve the desired formation in the presence of model uncertainties and disturbances. Moreover, by using the collision avoidance function, the mobile robots can avoid the obstacles successfully. Finally, simulations illustrate the effectiveness of the proposed control system.

In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.

This paper treats the DIS (Digital Image Stabilization) problem subject to base motions such as translation, rotation and zoom. For the local motion estimation from a raw image, the Harris corner detection algorithm is exploited to extract feature points, and comparing those of consecutive images, the zoom ratio (scale factor) is computed. For the global motion estimation, an equivalent model is derived to account for a 3-dimensional composite motion from which the center point and Euler angle can be determined. Finally, the motion compensation follows. To show the effectiveness of the present DIS scheme, experimental results for synthetic images are illustrated.

In this paper, we present a new type of spherical robot having two arms. This robot, called KisBot, mechanically consists of three parts, a wheel-shaped body and two rotating semi-spheres. In side of each semi-sphere, there exists an arm which is designed based on slider-crank mechanism for space efficiency. KisBot has hybrid types of driving mode: rolling and wheeling. In the rolling mode, the robot folds its arms through inside of itself and uses them as pendulum, then the robot works like a pendulum-driven robot. In the wheeling mode, two arms are extended from inside of the robot and are contacted to the ground, then the robot works like a one-wheel car. The Robot arms can be used as a brake during rolling mode and add friction to the robot for climbing a slope during wheeling mode. We developed a remote controlled type robot for experiment. It contains two DC motors which are located in the center of each semi-sphere for main propulsion, two RC motors for each arm operation, speed controllers for each semi-sphere, batteries for main power source, and other mechanical components. Experiments for the rolling and wheeling mode verify the hybrid driving ability and efficiency of the our proposed spherical robot.

When a robot navigates in an outdoor environment, a curb or a sidewalk separated from the road can be used as a robust feature. However, most algorithms could detect the curb only in the straight road, and could not detect highly curved corners, ramps, and so on. This paper proposes an algorithm which enables the robot to detect and follow the curbs in various types of roads. In the proposed method, the robot tilts a laser scanner and computes the error between the predicted and the measured distances to the road in front of the robot. Based on this error, the curbs at corners and curves can be classified. It is also difficult to detect a curb near a ramp because of its low height. In this case, the robot also tilts a laser scanner to detect the curb beyond the ramp. Once the robot classifies the road into the curve, corner, ramp, the robot selects the proper navigation strategies depending on the classified road types and is able to continue to detect and follow the curb. The results of a series of experiments show that the robot can stably detect and follows the curb in curves, corners and ramps as well as the straight road.

Today, the research related to the robot is achieved in various part. With the high interest in means of transport, various researches about autonomous mobile robot and next generation transport is continuing. The unicycle robot among these needs much control technique like balance control model and driving model. For autonomous driving of this unicycle robot, from the basic balance control to direction switching control and velocity control are needed. But the environment elements like a gradient and frictional force or unbalanced elements from the structural feature. The unicycle needs the real time balance control so more complex, harder to control. And when functional addition is made, the problem that fall entire reaction velocity or accuracy would be happen. This paper introduces entire dynamics modeling of the unicycle robot and reduced model. And propose the new balance control algorithm using fuzzy controller. Also the evaluation about performance would be made through the test.

In this paper, we propose a new gel-type biomimetic variable-focus lens system. The miniaturization of conventional lens system is limited due to the use of a set of glass lenses for adjusting the focal length. Biologically inspired by the focus adjustment mechanism of the human eye, a gel-type single lens system with variable-focus is presented. The proposed system consists of a gel-type lens, mechanical parts such as body, rotation ring, and winding-type SMA actuator. In addition, the proposed system is designed to operate with a simple and miniaturized mechanical structure using a new attachment and driving mechanism. The focusing performance of the proposed system is verified through a series of experiments and measurements of the shape of the lens using tomography.

We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

This paper proposes CDC (Continuous Damping Control) algorithm and verifies in multi-body dynamic vehicle. In order to distinguish a road profile on driving, waviness calculated by the filtered vertical-accelerations of sprung and unsprung masses is introduced. Sky-hook control is used at a low waviness road and constant damping level control is used at a high waviness road, where the hard damping level is determined by waviness, roll rate, acceleration, and deceleration. The damping levels of ride, anti-roll, anti-squat, and anti-dive modules are calculated by tuning parameters which is dependent upon vehicle velocity. Therefore this high tunable algorithm is useful to improve the ride and handling performance under various driving conditions. In the simulations, tire and dampers are modelled by SWIFT (Short Wavelength Intermediate Frequency Tire) model and 1st order delay model, and results are compared with conventional damper's.

This paper deals with the attitude control of an underactuated spacecraft that has fewer than three actuators. Even though such spacecrafts are known as uncontrollable, restricted missions are possible with controlling two-axis attitude angles. A variable speed control moment gyroscope is considered as an actuator. It is a kind of momentum exchange device and it shows highly nonlinear dynamical properties. Speed commands are generated by kinematic equations represented by Euler angles. A control law, that is designed to make a spacecraft follow the speed commands, is derived by the backstepping method. Angular speeds are estimated from the attitude measurements. Several estimation methods have been compared.

This paper present an effective complementary filtering method using encoder and gyro sensors for the self-localization(including heading and velocity) of indoor mobile robot. The main idea of the proposed approach is to find the pros and cons of each sensor through a various maneuvering tests and to design of an adaptive complementary filter that works for the entire maneuvering phases. The proposed method is applied to an indoor mobile robot and the performances are verified through extensive experiments.

This paper presents a foot movement tracking system using ultrasonic sensors and inertial sensors, where the position and velocity of foot are computed using inertial sensors and ultrasonic sensors mounted on a shoe. A foot movement can be estimated using an inertial navigation algorithm only; however, the error tends to increase due to biases of gyroscopes and accelerometers. To reduce the error, a localization system using ultrasonic sensors is additionally used. In the localization system using ultrasonic sensors, the position is continuously calculated in the absolute coordinate. An indirect Kalman filter is used to combine inertial sensors and ultrasonic sensors. Through experiments, it is shown that the proposed system can track a foot movement.

A fundamental characteristic of PMHT (Probabilistic Multi-Hypothesis Tracker) is that the number of targets and initial states of targets in the surveillance area must be a priori known. This requirement is impossible to fulfil in almost every realistic scenario. In the paper, we present two track initiation methods to solve the problem. The proposed track initiation methods are 2-point track initiation and Hough transform track initiation, and they are used to evaluate track initial states and weights for FTD (False Track Discrimination) of the PMHT algorithm. Also suggested as automatic target detection for tracking systems that combines track initiation for target detection with the PMHT algorithm for target tracking in a cluttered environment. A series of Monte-Carlo simulation runs is employed to evaluate the overall system performance with the two track initiation methods and the results are compared and analyzed.