The roof crane system is used for transporting a variable load to a target position. The goal of crane control system is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid tansportation is required. In this paper, we developed a simple fuzzy controller which has been introduced expert's knowledge base for anti-swing and rapid tranportation to goal position. In particular, we proposed the synthesis reasoning method which synthesizes on the basis of expert knowledge of the angle control input and position control input which are inferenced parallel and simultaneously. And we confirmed that the performance of the developed controller is effective as a result of applying it to crane simulator and also verified whether the proposed synthesis rules have been applied correctly using clustering algorithm from the measured data.

LQ-servo design procedure introduced by Athans is a method using a partial states feedback and an output feedback in order to improve the poor performance robustness of the LQR as well as to maintain its stability robustness. Although the method guarantees good stability robustness, it is not effective in performance robustness as it does not match the singular value at low or high frequencies of the transfer matrix obtained by breaking at the plant output. This paper intends propose of a new method, using the limited behaviour of the control gain introduced by Kwakernaak and Sivan, in order to improve it does it refer to controlga introduced by kwakernaak or the new metho Anblguouls.

본 논문에서는 볼테라 비선형 시스템의 선형화를 위한 새로운 적응 선행처리 기법을 제시한다. 특히, 제안된 적응 선행처리 기법은 (i) 순수 비선형 왜곡 보상을 위한 부분(pure nonlinear distortion compensator: PNDC)과, (ii) 선형 왜곡 보상을 위한 선형 역필터(linear inverse filter: LIF)의 두 부분으로 구성된다. 본 논문의 선형화 기법의 장점으로는 기존의 P차 역(Pth-order inverse) 기법에 비하여 계산량이 상당히 감소되며, 적응 알고리듬이 보다 빠르고 안정된 수렴 특성을 나타낸다. 끝으로, 모의실험을 통하여, 제안된 선행처리 기법의 성능및 실제 적용 가능성을 살펴본다.

This paper presents a recoil and counter recoil motion measurement method using linear variable differential transformers(LVDT). The output of a LVDT is obtained from the differential voltage of the 2nd transformers. As the sensor core is attached to the motion body, the output is directly proportional to the core motion. Displacement, velocity and acceleration are measured from the core length. A comparison between the measurement result and the known value, which is obtained by the precision steel tape, shows that the accuracy and the usefulness of the proposed scheme is validated.

A real-time collision-free trajectory control method for dual arm robot system is proposed. The proposed method is composed of two stages; one is to calculate the minimum distance between two robot arms and the other is to control the trajectories of the robots to ensure collision-free motions. The calculation of minimum distance between two robots is, also, composed of two steps. To reduce the calculation time, we, first, apply a simple modeling technique to the robots arms and determine the interested part of the robot arms. Next, we apply more precise modeling techniques for the part to calculate the minimum distance. Simulation results show that the whole algorithm runs within 0.05 second using Pentium 100MHz PC.

A method for solving the inverse kinematic problem of reclaimer is presented in this paper. The reclaimers in the raw yard are being used to dig raws and transfer them to the blast furnaces. The kinematic configuration of the reclaimer is different from that of commercially available robots, because it has a rotating disk with several buckets at the end of the boom to dig raws. The reclaimer has a redundancy due to the rotating disk : the degrees of freedom are greater than the number of forward kinematic equations. A plane equation in the 3-dimensional space is determined by using several points adjacent to the reclaiming point of the raw ores pile. A constraint is obtained from the relation ship of the plane equation and trajectories of the bucket of the reclaimer. Finally, a solution of the inverse kinematics of the reclaimer is determined by a numerical method.

본 논문에서는 비구동 관절을 가지는 2링크 매니퓰레이터의 동력학 해석과 운동제어를 제1적분을 기초로 하여 전개하고 있다. 매니퓰레이터의 운동이 제1적분의 적분상수에 의해서 기술되는 것을 보이고, 제1적분을 이용하여 매니퓰레이터의 동력학을 해석하고 있다. 그리고 해석된 동력학을 적극적으로 이용하는 운동제어 알고리즘을 구성하고 시뮬레이션을 통하여 확인하고 있다. 끝으로 비구동 관절에 마찰이 작용하는 경우, 브레이크등의 보조수단을 이용하지 않고도 매니퓰레이터의 제어가 가능함을 보이고 있다.

This paper presents the analysis of the kinematics and dynamics of redundant parallel manipulators, and provides design guides for advanced parallel mainpulators with high performance. Three types of redundancies are considered which include the redundancies in serial chain, joint actuation, and parallelism. First, the kinematic and dynamic models of a redundant parallel manipulator are obtained in both joint and Cartesian spaces, and the kinematic and dynamic manipulabilities are defined for the performance evaluation. The effects of the three types of redundancies on the kinematic and dynamic performance of a parallel manipulator are then analyzed and compared, providing a set of guides for the design of advanced parallel manipulators. Finally, the simulation results using planer parallel manipulators are given.

This paper describes a new process-plan selection method using a modified Fuzzy Quantification Theory(FQT). The problem of process-plan selection can be characterized by multiple attributes and used subjective, uncertain information. Fuzzy Quantification Theory is used for handling such information because it is a useful tool when human judgment or evaluation is quantified via linguistic variables, and the proposed method is concerned with the selection of a process plan by derivation of the values of categories for each attribute. In this paper, a modified Fuzzy Quantification Theory(FQT) is described and the procedure of this approach is explained and examples illustrated.

In this study an automatic rolling-coil labeling system using robot vision system and peripheral mechanism is proposed and implemented, which instead of the manual labor to attach labels Rolling-coils in a steel mill. The binary image process for the image processing is performed with the threshold, and the contour line is converted to the binary gradient which detects the discontinuous variation of brightness of rolling-coils. The moments invariant algorithm proposed by Hu is used to make it easy to recognize even when the position of the center are different from the trained data. The position error compensation algorithm of six degrees of freedom industrial robot manipulator is also developed and the data of the position of the center rolling-coils, which is obtained by floor mount camera, are transferred by asynchronous communication method. Therefore, even if the position of center is changed, robot moves to the position of center and performs the labeling work successfully. Therefore, this system can be improved the safety and efficiency.

기존에 있는 그룹테크놀로지의 방법들은 기계와 부품간의 공정유사성이나 그밖의 다른 정의의 유사성을 갖고 한 가지 정도의 알고리즘이나 수학적인 모델로써 해를 구했으나 그 해들은 실질적으로 현대 산업의 생산시스템이나 자동화에서 풀어나가야 하는 기계들의 병목현상을 풀어나가는 직접적인 접근방법을 제시하지 못했다. 따라서 본 연구에서는 새로운 기계간 유사성의 개발과 그래프이론을 응용한 알고리즘 그리고 수학적인 모델을 동시에 응용해서 병목현상을 초래하는 예외적인 원소의 재배치를 효과적이고 쉬운방법으로 제시하였다.

This paper presents the automatic recognition algorithm of the license number in on vehicle image. The proposed algorithm uses the correlation coefficient and Hough transform to detect license plate. The m/n ratio reduction is performed to save time and memory. By the correlation coefficient between the standard pattern and the target pattern, licence plate area is roughly extracted. On the extracted local area, preprocessing and binarization is performed. The Hough transform is applied to find the extract outline of the plate. If the detection fails, a smaller or a larger standard pattern is used to compute the correlation coefficient. Through this process, the license plate of different size can be extracted. Two algorithms to each separate number are proposed. One segments each number with projection-histogram, and the other segments each number with the label. After each character is separated, it is recognized by the neural network. This research overlomes the problems in conventional methods, such as the time requirement or failure in extraction of outlines which are due to the processing of the entire image, and by processing in real time, the practical application is possible.

This paper presents a fault detection and diagnosis methodology based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. In the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model is used to generate those candidates. The weight is determined from dynamic simulation. Using WSM, the methodology can generate the cause candidates and rank them according to the probability. Second, the fault propagation trends identified from the partial or complete sequence of measurements are compared with the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies, and the results showed satisfactory diagnostic resolution.

To control nonlinear chemical processes, a new neural linearizing control scheme is proposed. This is a hybrid of a radial basis function(RBF) network and a linear controller, thus the control action applied to the process is the sum of both control actions. Firstly, to train the RBF newtork a linear reference model is determined by analyzing the past operating data of the process. Then, the training of the RBF newtork is iteratively performed to minimize the difference between outputs of the process and the linear reference model. As a result, the apparent dynamics of the process added by the RBF newtork becomes similar to that of the linear reference model. After training, the original nonlinear control problem changes to a linear one, and the closed-loop control performance is improved by using the optimum tuning parameters of the linear controller for the linear dynamics. The proposed control scheme performs control and training simultaneously, and shows a good control performance for nonlinear chemical processes.

This article derives an analytic solution to determine the optimal size of multiple noncontinuous process and storage units. The total cost to be minimized consists of the setup cost of noncontinuous processing units and the inventory holding cost of feedstock/product storages. A novel approach, which is called PSW(Periodic Square Wave) model, is applied to represent the material flow among non-continuous units and storages. PSW model presumes that the material flow between unit and storage is periodic square wave shaped. The resulting optimal unit size has similar characteristics with the classical economic lot sizing model such as EOQ(Economic Order Quantity) or EPQ(Economic Production Quantity) model in a sense that the unit size is determined as the balance between setup and inventory holding cost. However, the influence of inventory holding cost of PSW model is different from that of EOQ/EPQ model. EOQ/EPQ model includes only the product inventory holding cost but PSW model includes all inventory holding costs around the non-continuous unit with proportional contribution. PSW model is suitable for analyzing interlinked process-storage system. The optimal lot size of PSW model is smaller than that of EOQ/EPQ model. This is quitea remarkable result considering that the EOQ/EPQ model has been is widely used since last half century.

In this paper, we present a resource conscious approach to designing distributed real-time systems as an extension of our original approach [8][9] which was limited to single processor systems. Starting from a given task graph and a set of end-to-end constraints, we automatically generate task attributes (e.g., periods and deadlines) such that (i) the task set is schedulable, and (ii) the end-to-end timing constraints are satisfied. The method works by first transforming the end-to-end timing constraints into a set of intermediate constraints on task attributes, and then solving the intermediate constraints. The complexity of constraint solving is tackled by reducing the problem into relatively tractable parts, and then solving each sub-problem using heuristics to enhance schedulability. In this paper, we build on our single processor solution and show how it can be extended for distributed systems. The extension to distributed systems reveals many interesting sub-problems, solutions to which are presented in this paper. The main challenges arise from end-to-end propagation delay constraints, and therefore this paper focuses on our solutions for such constraints. We begin with extending our communication scheme to provide tight delay bounds across a network, while hiding the low-level details of network communication. We also develop an algorithm to decompose end-to-end bounds into local bounds on each processor of making extensive use of relative load on each processor. This results in significant decoupling of constraints on each processor, without losing its capability to find a schedulable solution. Finally, we show, how each of these parts fit into our overall methodology, using our previous results for single processor systems.