In this paper, a novel sliding surface is proposed by defining a novel virtual state. This sliding surface has nominal dynamics of an original system and makes it possible that the sliding mode control(SMC) technique is used with the various types of controllers. Its design is based on the augmented system whose dynamics have a higher order than that of the original system. The reaching phase is removed by using an initial virtual state which makes the initial sliding function equal to zero.

An anti-reset windup (ARW) based compensation method for state constrained control systems is studied. First, a linear controller is constructed to give a desirable nominal performance ignoring state-constraints of a plant. Then, an additional compensator is introduced to provide smooth performance degradation under state-constraints of the plant. This paper focuses on the effective design method of the additional compensator. By minimizing a reasonable performance index, the proposed compensator is expressed in terms of theplant and ocntroller parameters. The resulting dynamics of the compensated controller exhibits the dominant part of the linear closed-loop system which can be seen from the singular perturbation model reducton theory. THe proposed method guarantees total stability of overall resulting systems if linear controllers were constructed to meet certain condition.

The nth-order, scalar, linear time-varying (LTV) systems can be dealt with operators on a differential ring. Using this differential algebraic structure and a classical result on differential operator factorizaitons developed by Floquet, a novel eigenstructure(eigenvalues, eigenvectors) concepts for linear time0varying systems are proposed. In this paper, Necessary and sufficient conditions for the existence of well-defined(free of finite-time singularities) SD- and PD- spectra for SPDOs with complex- and real-valued coefficients are also presented. Three numerical examples are presented to illustrate the proposed concepts.

This paper suggests a new image analysis method and indoor navigation control algorithm of mobile robots using a mono vision system. In order to reduce the positional uncertainty which is generated as the robot travels around the workspace, we propose a new visual landmark recognition algorithm with 2-D graph world model which describes the workspace as only a rough plane figure. The suggested algorithm is implemented to our mobile robot and experimented in a real corridor using extended Kalman filter. The validity and performance of the proposed algorithm was verified by showing that the trajectory deviation error was maintained under 0.075m and the position estimation error was sustained under 0.05m in the resultant trajectory of the navigation.

In this paper, the vibration suppression scheme based on a model referece approach is proposed. The vibration results from the coupling of the system and its frequency are given by the mechanical factors. In the proposed scheme, a low frequency vibration mode is transferred to high one. And also its damping ratio can be increased without any mechanical redesign. Therefore, bandwidth and open loop gain of the plant are increased and the performance of the system can be improved. This paper analyzes the proposed vibration suppression scheme, which is compared with the conventional control scheme for mechanical resonance suppression. For proving the realistic validity, we apply the proposed scheme to a LOS(Line Of Sight) stabilization system which has vibration effect. Finally, the proposed scheme is verified through simulations and experiments.

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

X-ray laminography and DT(digital tomosynthesis) that can form a cross-sectional image of 3-D objects promis to be good solutions for inspecting interior defects of industrial products. DT is a kind of laminography technique and the difference is in the fact that it synthesizes the several projected images by use of the digitized memory and computation. The quality of images acquired from the DT system varies according to image synthesizing methods, the number of images used in image synthesizing, and X-ray projection angles. In this paper, a new image synthesizing method named 'log-root method' is proposed to get clear and accurate cross-sectional images, which can reduce both artifact and blurring generated by materials out of focal plane. To evaluate the quality of cross-sectional images, two evaluating criteria : (1) shape accuracy and (2) clearness of the cross-sectional images are defined. Based on these criteria, a series of simulations are performed, and the results show the superiority of the new synthesizing method over the existing ones such as averaging and minimum methods.

Using a laser sheet beam projector combined with a CCD-Camera, an efficient technique to recognize complex surface of curvature and lane has been demonstrated for the purpose of mobile robot navigation. In general, obstacles of indoor environments in the field of SLIT-RAY plane are captured as segments of an elliptical arc and a line in the camera image. The robot has been capable of moving along around the obstacle in front of it, by recognizing the original shape of each segment with the differential coefficient by means of least squares method. In this technique, the imaged pixels of each segment, particularly elliptical arc, have been converted into a corresponding circular arc in the real-world coordinates so as to make more feasible the image processing for the position and radius measurement than conventional way based on direct elliptical are analyses. Advantages over direct elliptical cases include 1) higher measurement accuracy and shorter processing time because the circular arc process can reduce the shape-specifying parameters, 2) no complicated factor such as the tilt of elliptical arc axis in the image plane, which produces the capability to find column position and radiua regardless of the camera location . These are essentially required for a mobile robot application. This technique yields an accuracy less than 2cm for a 28.5cm radius column located in the range of 70-250cm distance from the robot. The accuracy obtained in this study is sufficient enough to navigate a cleaning robot which operates in indoor environments.

In this paper, the double inverted pendulum having a single actuator is built and the controller for the system is proposed. The lower link of the target pendulum system is hinged on the plate to free for rotation in the specified range($10^{\cire}$) on the x-z plane. The upper link is connected to the lower link through a DC motor. The double inverted pendulum built can be kept upright posture by controlling the position of the upper link even though it has no actuator in lower hinge. The algorithm to control the inverted pendulum consists of a state feedback controller within a linearizable range and a fuzzy logic controller coupled with a nonlinear feedback compensator for the rest of the range. Conventional state feedback control is employed, and the fuzzy controller is responsible for generating the reference joint angle of the upper link for the nonlinear feedback compensator which drives a DC motor to generate an indirect torque to the lower joint. As a result, we can get the upright posture of the proposed pendulum system. Simulations and experiments are conducted to show the validity of the proposed controller.

A new paradigm of technology, based on the overall interactions of technology, human and environment, is explored. History of technology and machines is reviewed in terms of the interactions of human and machines. Two main concepts of intelligent interactions proposed, holism and embodiment, are based on the interactions of machines and human through human body : Korperlichkeit ( corporeality). Human body movements are the result of long periods of evolution and, thus, are very optimized motions. Complicated and flexible motions could be easily achieved by mimicking human body movements. Motion capture and mimic systems based on the electromagnetic, visual, and gyroscopic type trackers, are being implemented to demonstrate these concepts. Also, various motion mappings are investigated on these interactive systems. By exploring a new paradigm of technology through Korperlichkeit, an oriental view of technology as relativities may evolve to embrace the limitations of western view of machines as an absolute independent form.

A mobile robot in FMS environment should be able to nevigate itself. Therefore, path planning is necessary for the mobile robot to perform its tasks without being lost. Path planning using a network model gives oprimal paths to every pair of nodes but building this model demands accurate information of environments. In this paper, a method to build a network model using sonar sensors is presented. The main idea is to build a quad tree model by using sonar sensors and convert the model to a network model for path planning. The new method has been implemented on a mobile robot. Experimental results show that the mobile robot constructs an accurate network model using inaccurate sonar data.

This paper focuses on development of a performance manager for IEEE 802.4 token bus networks to serve large-scale integrated systems. In order to construct the management algorithm, the principles of fuzzy logic, genetic algorithm, and neural network have been combined to represent human knowledge and to imitate of human inference mechanism. Through the simulation experiments, it is shown that the proposed performance manager is capable of improving the network performance without a priori knowledge.

In this paper, the analytical appproaches are presented for jointly determining the profit-miximizing configuration of the fault-tolerance real time modular cell manufacturing system. The transient(time-dependent) analysis of Markovian models is firstly applied to modular cell manufacturing system from a performability viewpoint whose modeling advantage lies in its ability to express the performance that truly matters - the user's perception of it - as well as various performance measures compositely in the context of application. The modular cells are modeled with hybrid decomposition method and then availability measures such as instantaneous availability, interval availability, expected cumulative operational time are evaluated as special cases of performability. In addition to this evaluation, sensitivity analysis of the entire manufacturing system as well as each machining cell is performed, from which the time of a major repair policy and the optimal configuration among the alternative configurations of the system can be determined. Secondly, the recovery policies from the machine failures by computing the minimal number of redundant machines and also from the task failures by computing the minimum number of tasks equipped with detection schemes of task failure and reworked upon failure detection, to meet the timing requirements are optimized. Some numerical examples are presented to demonstrate the effectiveness of the work.

This paper discusses a real time multi-tasking system model and a development environment for an elevator control system. Recently, as the elevator systems become large-scaled and operate with high speed, there are lots of software tasks to be processed with time constraints. Thus, the control systems are designed with distributed control structure and characteristics of typical real time systems. For stuructural design of such real time system, we introduce a multi-tasking model based on a real time operating system model and an software development environment based on virtual protopyping which simulates real system operation in the cross development of a new elevator system with distributed control structure and its system reliability can be verified through numerous field tests.

To achieve fast loading and unloading of containers from a container ship, quick suppression of the remaining sway motion of the container at the end of each trolley stroke is crucial. Due to the pendulum motion of the container and disturbances like sind, residual sway always exists at the end of trolley movement. In this paper, the sway-control problem of a container crane is investigated. A two-stage control is proposed. The first stage is a time optimal controlfor the purpose of fast trolley traveling. The second stage is a nonlinear control for the quick suppression of residual sway, which starts right after the first stage while lowering the container. The nonlinear control is investigated in the perspective of controlling an underatuated mechanical system, which combines partial feedback linearization to account for the known nonlinearities as much as possible, and variable structure control to account for the unmodeled dynamics and disturbances. Simulation and experimental results are provided.