This paper will introduce the development case study about virtual-reality-based operation training system for steel making process. Steel making process consist iron making process to create liquid steel, pig iron, by reduction process, steel making process to make molten steel by refining, continuous casting process to make slab, and rolling process to make final product like coil, plate. This steel making process deals with liquid and solid products, so facilities of steel making process are very various and complicated. In addition, according to various customer requirements, the recycle of facilities and recipes changing have been fast. So the training for skilled operators is very important point. In this paper, we develop steel making training system based virtual reality for training skilled operator. This system consists of virtual machine, virtual HMI, and virtual control panel. And for fitting the characteristics of each process and increasing the education effectiveness, we develop dynamic methods like the method of dynamic education system configuration, initial facilities setup operation education system, and etc.

In this paper, we propose camber monitoring system which is using on hot rolling process. In roughing mill which is one of the rolling part in hot rolling process, steel plate can be bended in width direction under the imbalance of rolling condition. This bending of steel plate in width direction is called as camber. In order to measure the camber, first, cameras which are installed over transport pathway of steel plate take pictures of whole shape of steel plate. And location value of steel plate edge is extrated from these pictures by edge detection algorithm. But, there are a lot of noises which are generated by such as water sprays, dusts, peripheral equipments in these pictures, and these noises make edge detection difficult. In order to solve this kind of problem, we developed a direction selective edge detection algorithm, and applicated in our camber monitoring system. As a result, we got stable results in spite of process noises.

This paper proposes a fractional-order PID (Proportional-Integral-Derivative) control used electromagnetic strip stabilization controller in a continuous galvanizing line. Compared to a conventional PID controller, a fractional-order PID controller has integration-fractional-order and derivation-fractional-order as additional control parameters. Thanks to increased control parameters, more precise controller adjustment is available. In addition, accurate transfer function of a real system generally has a fractional-order form. Therefore, it is more adequate to use a fractional-order PID controller than a conventional PID controller for a real world system. Finite element models of a $1200{\times}2000{\times}0.8mm$ strip, which were extracted using a commercial software ANSYS were used as simulation plants, and Gaussian mixture models were used to find optimized control parameters that can reduce the strip vibrations to the lowest amplitude. Simulation results show that a fractional-order PID controller significantly reduces strip vibration and transient response time than a conventional PID controller.

In the conventional hot rolling process, the defects of products such as scratches occur due to impact and friction. Impact occurs as a result of the contact of between rollers and the slab. Also, friction occurs in the rolling process. To improve these defects, a variety of processes were developed. The flying touch method is also one of the processes to reduce defects and uses a movable upper roller. To use this unfixed roller, the impact and frictions between rollers and the slab should be minimized. This paper proposes a hot rolling process simulator to verify and test the efficiency of the flying touch method. The simulator was designed to verify the method. This paper also proposes a new impact reducing method and velocity synchronization method which are simulated to realize the method.

Improvement in the control strategy for continuous casting is a crucial requirement to enhance the slab's quality and to increase productivity. The mold oscillator adopts the dual cylinders due to its heavy weight, so the synchronized motion of two cylinders is an important aspect when precise control is needed. The conventional method uses the master-slave control applied to the valve input reference, but the synchronization performance should still be improved. This paper proposes a novel synchronization algorithm for dual cylinders used in a mold oscillator. The master-slave concept is applied to the target reference position, that is, the slave target reference position is controlled to match the slave cylinder's position with the master cylinder's position. In the simulation based on a Simulink model, the proposed algorithm shows a better synchronization performance in aspect of the mean of the absolute error and the peak synchronization error.

In this paper, we suggest a dimensional controller to produce a different thickness strip without adding production facilities at the same steel. We describe the model for the non-linear thickness and speed setup, and drive a variation of the speed and thickness with Talyor expansion. The control algorithm is composed of 8 steps and the transient condition is added in order to maintain a mass flow between stands. A simulator is developed in order to verify the algorithm, and includes a non-linear rolling model, the tension model, AGC model, the disturbance model, and so on. From the simulation results by disturbances, we show that the thickness, tension and looper angle are converged to the set condition when we change the rolling conditions.

The quality of steel plate products is determined by the number of defects and the process problems are estimated by shapes of defects. Therefore pinholes defects of cold rolled steel have to be controlled. In order to improve productivity and quality of products, within each production process, the product is inspected by an adequate inspection system individually in the lines of steelworks. Among a number of inspection systems, we focus on the pinholes detection system. In this paper, we propose an embedded system using FPGA which can detect pinholes defects. The proposed system is smaller and more flexible than a traditional system based on expensive frame grabbers and PC. In order to detect consecutive defects, FPGAs acquire two dimensional image and process the image in real time by using correlation of lines. The proposed pinholes detection algorithm decreases arithmetic operations of image processing and also we designed the hardware to shorten the data path between logics due to decreasing propagation delay. The experimental results show that the proposed embedded system detects the reliable number of pinholes in real time.

We present an output feedback controller for a class of nonlinear systems with uncertain nonlinearity and sensor noise. The sensor noise has both a finite constant component and a time-varying component such that its integral function is finite. The new design and analysis method is based on the matrix inequality approach. With our proposed controller, the states and output can be ultimately bounded even though the structure of nonlinearity is more general than that in the existing results.

This paper introduces an experimental rescue robot, HUBO T-100 and presents the optimal motion control method. The objective of the rescue robot is to extract patients or wounded soldiers in the battlefield and hazardous environments. Another mission is to dispose and transport an explosive ordnance to safe places. To execute these missions, the upper body of the rescue robot is humanoid in form to execute various kinds of tasks. The lower body features a hybrid tracked/legged design, which allows for a variety of mode of locomotion, depending on terrain conditions in order to increase traversability. The weight lifting motion is one of the most important task for performing rescue related missions because the robot must lift an object or impaired person lying on the ground for transferring. Here, dynamics based motion optimization is employed to minimize joint torques while maintaining stability simultaneously. Physical experiments with a real humanoid robot, HUBO T-100, are presented to verify the proposed method.

This paper proposes an attitude control system to keep the balance for a two-wheeled mobile manipulator which consists of a mobile platform and a three D.O.F. manipulator. In the conventional control scheme, complicated dynamics of the manipulator need to be derived for balancing control of a mobile manipulator. The method proposed in this paper, however, three links are considered as one body of mass and the dynamics are derived easily by using an inverted pendulum model. One of the best advantage of a sliding mode controller is low sensitivity to plant parameter variations and disturbances, which eliminates the necessity of exact modeling to control the system. Therefore the sliding mode control algorithm has been adopted in this research for the attitude control of mobile platform along the pitch axis. The center of gravity for the whole mobile manipulator is changing depending on the motion of the manipulator. And the orientation variation of center of gravity is used as reference input for the sliding mode controller of the pitch axis to maintain the center of gravity in the middle of robot to keep the balance for the robot. To confirm the performance of controller, MATLAB Simulink has been used and the resulting algorithms are applied to a real robot to demonstrate the superiority of the proposed attitude control.

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

This paper proposes a hybrid visual servoing algorithm for the object tracking by a mobile robot with the stereo camera. The mobile robot with the stereo camera performs an object recognition and object tracking using the SIFT and CAMSHIFT algorithms for the hybrid visual servoing. The CAMSHIFT algorithm using stereo camera images has been used to obtain the three-dimensional position and orientation of the mobile robot. With the hybrid visual servoing, a stable balance control has been realized by a control system which calculates a desired angle of the center of gravity whose location depends on variations of link rotation angles of the manipulator. A PID controller algorithm has adopted in this research for the control of the manipulator since the algorithm is simple to design and it does not require unnecessary complex dynamics. To demonstrate the control performance of the hybrid visual servoing, real experiments are performed using the mobile manipulator system developed for this research.

This paper proposes a path planning algorithm to reduce the inspection time of AOI (Automatic Optical Inspection) machines for SMT (Surface Mount Technology) in-line system. Since the field-of-view of the camera attached at the machine is much less than the entire inspection region of board, the inspection region should be clustered to many groups. The image acquisition time depends on the number of groups, and camera moving time depends on the sequence of visiting the groups. The acquired image is processed while the camera moves to the next position, but it may be delayed if the group includes many components to be inspected. The inspection delay has influence on the overall job time of the machine. In this paper, we newly considers the inspection delay time for path planning of the inspection machine. The unified approach using genetic algorithm is applied to generates the groups and visiting sequence simultaneously. The chromosome, crossover operator, and mutation operator is proposed to develop the genetic algorithm. The experimental results are presented to verify the usefulness of the proposed method.

This paper describes the design for a defective product inspection device for the curved glass used in smart-phone. Cameras are used as inspection devices to find cracks in LCDs (Liquid Crystal Displays), PDPs (Plasma Display Panels), etc. The devices used to inspect the curved glass used in smart-phone consist of a camera, two back-light apparatus, an inspection apparatus main body, and an image processing program. Camera image calibration was performed to smooth an image taken with the camera, and as a result, the average error was less than 0.12 pixels. And the image of a smart-phone's curved glass taken with the camera was processed using the produced program. As a result, the program could correctly extract the cracks on the curved glass. Thus, it is thought that the designed inspection device can successful detect cracks in curved tempered glass.