This paper proposes the state observer design for nonlinear systems with delayed output. It is shown that by considering a nonlinear term of error dynamics as an additional state variable, the nonlinear error dynamics with time delay can be transformed into the linear one with time delay. Sufficient conditions for existence of a state observer are characterized by linear matrix inequalities. Finally, an illustrative example is given in order to show the effectiveness of our design method.

This paper studies asymptotic consensus problem for linear multi-agent systems. We propose a distributed state feedback control algorithm for solving the problem under fixed and undirected network communication. In contrast with the conventional algorithms that use global information (e.g., graph connectivity), the proposed algorithm only uses local information from neighbors. The principle for achieving asymptotic consensus is that, for each agent, a distributed update law gradually increases the coupling gain of LQR-type feedback and thus, the overall stability of the multi-agent system is recovered by the gain margin of LQR.

This paper presents synchronization of LTV (Linear Time-Varying) MAS (Multi-Agent Systems) with heterogeneous time-varying disturbances under a fixed, connected, and undirected communication network. All the agents can collect only relative state information from their neighborhoods. To achieve synchronization of the MAS, an integral control scheme is proposed based on relative state information between agents.

Observable mathematical model of DDM (Direct Dirve Motor) was suggested. The motor that operates the object system directly is called DDM. DDM has many strong points, however, it has a significant disadvantage, that it is more sensitive to the external force than the motor with reduction gear. In other word, if the force is applied, air gap of the motor can be perturbed. This causes not only difficulty in motor control but also even more serious problem, such as the breakdown of motor. However, if the air gap variation can be estimated, it can help prevent these problems. DDM should be modeled to estimate the air gap variation. The type of researched DDM is PMSM (Permanent Magnet Synchronous Motor) and precedent model of PMSM includes only characteristics of electro-magnetic system and rotational motion. However, suggested model should also include characteristics of translational motion of rotor to estimate the air gap variation. Also, this model should satisfy observability condition, because state observer is designed based on this model.

This paper introduces a simple and efficient calibration method for three-axis accelerometers and three-axis gyroscopes using three-axis motion rate table. Usually, the performance of low cost MEMS-based inertial sensors is affected by scale and bias errors significantly. The calibration of these errors is a bothersome problem, but the previous calibration methods cannot propose simple and efficient method to calibrate the errors of three-axis inertial sensors. This paper introduces a new simple and efficient method for the calibration of accelerometer and gyroscope. By using a three-axis motion rate table, this method can calibrate the accelerometer and gyroscope simultaneously and simply. Experimental results confirm the performance of the proposed method.

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

This paper proposes the gait phase classifier using backpropagation neural networks method which uses the angle of lower body's joints and ground reaction force as input signals. The classification of a gait phase is useful to understand the gait characteristics of pathologic gait and to control the gait rehabilitation systems. The classifier categorizes a gait cycle as 7 phases which are commonly used to classify the sub-phases of the gait in the literature. We verify the efficiency of the proposed method through experiments.

An effective dual-mode camera system(a passive wide-angle camera and a pan-tilt-zoom camera) is proposed in order to improve the performance of visual surveillance. The fixed wide-angle camera is used to monitor large open areas, but the moving objects on the images are too small to view in detail. And, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a specific moving target. However, its FOV (Field of View) is limited when zooming in on a specific target. Therefore, the cooperation of wide-angle and PTZ cameras is complementary. In this paper, we propose an automatic initial set-up algorithm and coordinate transform method from the wide-angle camera coordinate to the PTZ one, which are necessary to achieve the cooperation. The automatic initial set-up algorithm is able to synchronize the views of two cameras. When a moving object appears on the image plane of a wide-angle camera after the initial set-up positioning, the obtained values of the wide-angle camera should be transformed to the PTZ values based on the coordinate transform method. We also develope the PTZ control method. Various in-door and out-door experiments show that the proposed dual-camera system is feasible for the effective visual surveillance.

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

Hierarchical IPP (Integrated Path Planning) combining the GPP (Global Path Planner) and the LPP (Local Path Planner) is interesting the researches who study about the mobile vehicle in recent years. However, in this study, there is the path mismatch problem caused by the difference in the map information available to both path planners. If ever a part of the path that was found by the GPP is available to mobile vehicle, the part may be unavailable when the mobile vehicle generates the local path with its built-in sensors while the vehicle moves. This paper proposed the TWR (Temporal Waypoint Reviser) to solve the path mismatch problem of the hierarchical IPP. The results of simulation provide the performance of the IPP with the TWR by comparing with other path planners.

This paper investigates an algorithm for robust fault diagnosis in robot manipulators. The TOSM (Third Order Sliding Mode observer) provides both theoretically exact observation and unknown fault identification without filtration. The EOI (Equivalent Output Injections) of the TOSM observers can be used as residuals for the problem of fault diagnosis and to identify the unknown faults. The obtained fault information can be used for fault detection, isolation as well as fault accommodation to the self-correcting failure system. The computer simulation results for a PUMA 560 robot are shown to verify the effectiveness of the proposed strategy.

This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

One of the frequent problems in the stabilized gimbal system is the rejection of disturbances associated with moving components. Very often such disturbances have non-linear characteristics. In a typical gimbal system, each gimbal and platform are connected by a mutual bearing which induces inevitable friction. Particularly, the non-linear Coulomb friction causes position errors as well as slow responses that lead to unfavorable performance. In this paper, a modified PID controller that is augmented by Coulomb friction estimator is presented. Through constantly estimating the Coulomb friction torque, it is applied to the output of the existing PID controller. The effectiveness of the proposed controller is evaluated through a series of experiments.

This paper deals with ROLSO (Reduced Order Luenberger State Observer) design to prevent jackknifing phenomenon of articulated vehicles consisting of the tractor and semi-trailer by using GPS. In addition, by applying the regulator system using ROLSO feedback system, simulation's result presents that articulated vehicle's states are stabilized than the human's PR time (Preception Response time) rapidly. This simulation verifies that the automatic control of articulated vehicle's can be applied for the accident prevention for the time that the driver is unable to manage with the sudden accident. For this simulation, by using the equation of planar motion, the modeling of the articulated vehicle was performed. This modeling was expressed in the state space model. And FOLSO (Full Order Luenberger State Observer), ROLSO were designed by using the state space model of an articulated vehicle's dynamics.