This paper presents the guidance and control design for automatic carrier landing of a UAV (Unmanned Aerial Vehicle). Differently from automatic landing on a runway on the ground, the motion of a carrier deck is not fixed and affected by external factors such as ship movement and sea state. For this reason, robust guidance/control law is required for safe shipboard landing by taking the relative geometry between the UAV and the carrier deck into account. In this work, linear quadratic optimal controller and longitudinal/lateral trajectory tracking guidance algorithm are developed based on a linear UAV model. The feasibility of the proposed control scheme and guidance law for the carrier landing are verified via numerical simulations using X-Plane and Matlab/simulink.

Unmanned flying robots have been used recently in many difficult situations. One of the major issues in this area is the problem of how long these unmanned flying robots can perform a given task successfully. For this, the development of a light body and high-efficiency power supply has been executed widely, but we do not as yet have the complete solution. In this paper, we propose a form of Multi-Copter X8, which can transform into other types to further improve these problems. The proposed robot has a 3-type modification capability, which can produce a more enhanced energy saving effect by reducing power consumption.

Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.

The results of control law design for a tilt-rotor unmanned aerial vehicle that has a nacelle mounted wing extension (WE) are presented in this paper. It consists of a control surface mixer, stability and control augmentation system (SCAS), hold mode for altitude / speed / heading, and a guidance mode for preprogram and point navigation which includes automatic take-off and landing. The conversion corridor and the control moments derivatives between the original tilt-rotor and its variant of the nacelle mounted WE were compared to show the effectiveness of the WE. The nacelle conversion of the original tilt-rotor starts when the airspeed is greater than 30 km/h but its WE variant starts at 0 km/h in order to reduce the drag caused by the high incidence angle of the WE. The stability margins of the inner loop are presented with the optimization approach. The outer loops for the hold mode are designed with trial and error methods with linear and nonlinear simulation. The main control parameter for altitude control of the helicopter mode is thrust command and it is transferred to the pitch attitude command in airplane mode. Otherwise, the control parameter for the speed of the helicopter mode is the pitch attitude command and it is transferred to the thrust command in airplane mode. Therefore the speed and altitude hold mode are coupled to each other and are engaged at the same time when an internal pilot engages any of the altitude or speed hold modes. The nonlinear simulation results of the guidance control for the preprogrammed mode and point navigation are also presented including automatic take-off and landing in order to prove the full control law.

Unmanned aerial vehicles (UAVs) are a popular research topic because of a great ripple effect in the future. However, current UAV technologies cannot be applied to manual aerial vehicles without any modification. As an alternative to current UAV technology, humanoid robots are adopted as pilots. If a humanoid robot controls an aerial vehicle autonomously, not only could manual aerial vehicles be utilized as UAVs, but the humanoid robot would also be put into an environment created for humans and conduct some missions suitable for humans. Humanoid robots are also able to handle tools and equipment designed for humans. In order to prove that a humanoid robot can pilot an airplane, an experiment is performed and the results of this experiment are shown in this paper.

This paper proposes a novel controller design scheme for multimachine power systems based on the explorized policy iteration. Power systems have several uncertainties on system dynamics due to the various effects of interconnections between generators. To solve this problem, the proposed method solves the LQR (Linear Quadratic Regulation) problem of isolated subsystems without the knowledge of a system matrix and the interconnection parameters of multimachine power systems. By selecting the proper performance indices, it guarantees the stability and convergence of the LQ optimal control. To implement the proposed scheme, the least squares based online method is also investigated in terms of PE (Persistency of Excitation), interconnection parameters and exploration signals. Finally, the performance and effectiveness of the proposed algorithm are demonstrated by numerical simulations of three-machine power systems with governor controllers.

In this paper, we discuss the relation between the motion profile and pre-filter. As previously reported in various literatures [1-3], a tuned motion profile can effectively reduce residual vibration by placing inherent zeros of the motion profile at the vibratory pole of systems similar to the role of the input shaping technique. From the results, we factorize the motion profile into a basis function and an input shaper. In contrast to the previously reported impulse-sequence-based input shapers, the input shaper extracted from the motion profile has unique characteristics. Thanks to the characteristics of the input shaper extracted from the motion profile, it has advantages to reduce the vibrations caused by not only the modeled vibratory mode but also unmodeled dynamics which exist in higher frequency ranges.

This paper proposes the enhanced faulty node detection scheme with hybrid algorithm using Markov-chain model on BCH (Bose-Chaudhuri-Hocquenghem) code in naval distributed control networked systems. The probabilistic model-driven approach, on Markov-chain model, in this paper uses the faulty weighting interval factors, which are based on the BCH code. In this scheme, the master node examines each slave-nodes continuously using three defined states : Good, Warning, Bad-state. These states change using the probabilistic calculation method. This method can improve the performance of detecting the faulty state node more efficiently. Simulation results show that the proposed method can improve the accuracy in faulty node detection scheme for real-time naval distributed control networked systems.

This paper proposes a new contact type ball tracking sensor to improve the control performance of a low cost ball-and-beam system. It is well-known that the impulsive measurement noise contained in ball position measurement is one of the factors which severely degrades the ball-and-beam control performance. The impulsive ball position measurement noises often appear under the sporadical ball floating on the beam. This fact motivates us to devise a simple analog preprocessing circuit to determine whether the ball loses the contact or not. Once the abnormal ball position measurement is detected, the design problem of the ball tracking sensor can be cast into the typical state estimation problem with missing data. In order to tackle the real-time implementation issue, a steady-state Kalman filter is applied to the problem. Through the experimental results, the usefulness of the proposed scheme is demonstrated.

This paper addresses on a $H_{\infty}$ sampled-data stabilization of a Takagi-Sugeno (T-S) fuzzy system. The sampled-data stabilization problem is formulated as a discrete-time stabilization one via a direct discrete-time design approach. It is shown that the sampled-data fuzzy control system is asymptotically stable whenever its exactly discretized model is asymptotically stable. Based on an exact discrete-time model, sufficient design conditions are derived in the format of linear matrix inequalities (LMIs). An example is provided to illustrate the effectiveness of the proposed methodology.

This paper describes the design of a four-axis force/torque sensor with PSPBs (Parallel Step Plate Beams). The sensor is composed of eight PSPBs, a force/torque transmitting block, and fixing blocks. It is designed by using the FEM(Finite Element Method), and fabricated by using strain gages. The characteristic tests of the sensor are carried out, and the interference error, repeatability error, and non-linearity error are less than 2.21%, 0.03% and 0.03%. Furthermore, the structure of the four-axis force/torque sensor with PSPBs has a larger rated capacity than that of the four-axis force/torque sensor with PPBs under the same overall sensor size and the same rated output. It is thought that the developed four-axis force/torque sensor with PSPBs can be used for measuring the forces and torques in an intelligent robot, automation devices, etc.

An efficient 3D SLAM (Simultaneous Localization and Map Building) method is developed for urban building environments using a tilted 2D LRF (Laser Range Finder), in which a 3D map is composed of perpendicular/horizontal planar polygons. While the mobile robot is moving, from the LRF scan distance data in each scan period, line segments on the scan plane are successively extracted. We propose an "expected line segment" concept for matching: to add each of these scan line segments to the most suitable line segment group for each perpendicular/horizontal planar polygon in the 3D map. After performing 2D localization to determine the pose of the mobile robot, we construct updated perpendicular/horizontal infinite planes and then determine their boundaries to obtain the perpendicular/horizontal planar polygons which constitute our 3D map. Finally, the proposed SLAM algorithm is validated via extensive simulations and experiments.

This paper proposes an angle estimation of Segway robot for the slop driving. Most of Segway robot was controlled by pose control of keeping robot's balance and motor control of driving. In motor control, we analyzed Segway robot kinetically and estimated an angle of inclination using the velocity that depends on input force. In pose control, also, we used PD controller and evaluated a stability of controller through MATLAB simulation. Assuming the robot keeps its balance stably using controller, we could linearize dynamics. We could obtain the result through the experiment which estimates an angle using the velocity of Segway robot that is derived from linearized dynamics.

This paper suggests using the ICP (Iterative Closet Point) algorithm to compensate a two-dimensional map. ICP algorithm is a typical algorithm method using matching distance data. When building a two-dimensional map, using data through the value of a laser scanner, it occurred warping and distortion of a two-dimensional map because of the difference of distance from the value of the sensor. It uses the ICP algorithm in order to reduce any error of line. It validated the proposed method through experiment involving matching a two-dimensional map based reference data and measured the two-dimensional map.

This paper proposes a new technique that produces improved local information using a low-cost GPS/INS system combined with Extended Kalman Filter and Path Planning when a Quad-rotor flies. In the research, a low-cost GPS is combined with INS by Extended Kalman Filter to improve local information. However, this system has disadvantages in that estimation accuracy is getting worsens when the Quad-rotor flies through the air in a curve and precision of location information is influenced by performance of the used GPS. An algorithm based on Path Planning is adopted to deal with these weaknesses. When the Quad-rotor flies outdoors, a short moving path can be predicted because all short moving paths of quad-rotor can be assumed to be straight. Path planning is used to make the short moving path and determine the closest local information of data of the GPS/INS system to location determined by path planning. Through the foregoing process, improved local data is obtained when the quad-rotor flies, and the performance of the proposed system is verified from various outdoor experiments.