This paper presents the modeling and multivariable feedback control of a novel high-precision multi-dimensional positioning stage. This integrated 6-degree-of-freedom. (DOF) motion stage is levitated by three aerostatic bearings and actuated by 3 three-phase synchronous permanent-magnet planar motors (SPMPMs). It can generate all 6-DOF motions with only a single moving part. With the DQ decomposition theory, this positioning stage is modeled as a multi-input multi-output (MIMO) electromechanical system with six inputs (currents) and six outputs (displacements). To achieve high-precision positioning capability, discrete-time integrator-augmented linear-quadratic-regulator (LQR) and reduced-order linearquadratic-Gaussian (LQG) control methodologies are applied. Digital multivariable controllers are designed and implemented on the positioning system, and experimental results are also presented in this paper to demonstrate the stage's dynamic performance.

In this paper, moving a fragile object from an initial point to a specific location in the minimum time without damage is studied. In order to achieve this goal, initially, the maximum acceleration and velocity ranges are specified. These ranges can be dynamically generate on the planned path by the manipulator. The path can be altered by considering the geometrical constraints. Later, considering the impulsive force constraint on the object, the range of maximum acceleration and velocity are obtained to preserve object safety while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of acceleration and velocity. This time-optimal trajectory planning can be applied to real applications and is suitable for both continuous and discrete paths.

A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.

The goal of this work is to develop and test a robot-assisted surgery system for spinal fusion. The system is composed of a robot, a surgical planning system, and a navigation system. It plays the role of assisting surgeons for inserting a pedicle screw in the spinal fusion procedure. Compared to conventional methods for spinal fusion, the proposed surgical procedure ensures minimum invasion and better accuracy by using robot and image information. The robot plays the role of positioning and guiding needles, drills, and other surgical instruments or conducts automatic boring and screwing. Pre-operative CT images intra-operative fluoroscopic images are integrated to provide the surgeon with information for surgical planning. Some experiments employing the developed robotic surgery system are conducted. The experimental results confirm that the system is not only able to guide the surgical tools by accurately pointing and orienting the specified location, but also successfully compensate the movement of the patient due to respiration.

In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.

In this paper, ATM network congestion control with explicit rate feedback is considered. In ATM networks, delays commonly appear in data transmission and have to be considered in congestion control design. In this paper, a bounded single round delay on the return path is considered. Our objective is to design an explicit rate feedback control that achieves a robust optimal $H_2$ performance regardless of the bounded time-varying delays. An optimization approach in terms of linear matrix inequalities (LMIs) is given. Saturation in source rate and queue buffer is also taken into consideration in the proposed design. Simulations for the cases of single source and multiple sources are presented to demonstrate the effectiveness of the design.

Problems like poor security, transfer delay or packet loss occur while building network systems that are applied with TCP/TP integrate with data network systems. To solve this problem, this paper proposes the Separated Ethernet, which can give priority to the system, and by using the OPNET Modeler simulator, we will verify its performances.

The objective of this paper is to propose a reference model of a fire detection and monitoring system using MS/TP protocol. The reference model is designed to satisfy the requirements of response time and flexibility. The reference model is operated on the basis of BACnet, a standard communication protocol for building automation systems. Validity of the reference model was examined using a simulation model. This study also evaluated the performance of the BACnet-based fire detection and monitoring system in terms of network-induced delay. Simulation results show that the reference model satisfies the requirements of the fire detection and monitoring system.

A new method in robot path generation is presented using an analysis of the characteristics of multi-robot collision avoidance. The research is based on the concept of the collision map, where the collision between two robots is presented by a collision region and a crossing curve TLVSTC (traveled length versus servo time curve). Analytic collision avoidance is considered by translating the collision region in the collision map. The 4 different translations of collision regions correspond to the 4 parallel movements of the actual original robot path in the real world. This analysis is applied to path modifications where the analysis of collision characteristics is crucial and the resultant path for collision avoidance is generated. Also, the correlations between the translations of the collision region and robot paths are clarified by analyzing the collision/non-collision areas. The influence of the changes of robot velocity is investigated analytically in view of collision avoidance as an example.

The outlet feeder pipe thinning in a PHWR (Pressurized Heavy Water Reactor) is caused by a high pressure steam flow inside the pipe, which is a well known degradation mechanism called a FAC (Flow Assisted Corrosion). In order to monitor the degradation, the thickness of the outlet bends close to the exit of the pressure tube should be measured and analyzed at every official overhaul. This paper describes a mobile feeder pipe inspection robot that can minimize the irradiation dose to human workers by automating the measurement process. The robot can move by itself on the feeder pipe by using an inch worm mechanism, which is constructed by two gripper bodies that can fix the robot body on to the pipe, one extendable and contractible actuator, and a rotation actuator connected to the two gripper bodies to move forward and backward, and to rotate in a circumferential direction.

We propose a path planning method to improve the productivity of AOI (automated optical inspection) machines in PCB (printed circuit board) assembly lines. The path-planning problem is the optimization problem of finding inspection clusters and the visiting sequence of cameras to minimize the overall working time. A unified method is newly proposed to determine the inspection clusters and visiting sequence simultaneously. We apply a hybrid genetic algorithm to solve the highly complicated optimization problem. Comparative simulation results are presented to verify the usefulness of the proposed method.

The main function of a reactor protection system is to maintain the reactor core integrity and the reactor coolant system pressure boundary. Generally, the reactor protection system adopts the 2-out-of-m redundant architecture to assure a reliable operation. This paper describes the safety assessment of a digital reactor protection system using the fault tree analysis technique. The fault tree technique can be expressed in terms of combinations of the basic event failures such as the random hardware failures, common cause failures, operator errors, and the fault tolerance mechanisms implemented in the reactor protection system. In this paper, a prediction method of the hardware failure rate is suggested for a digital reactor protection system, and applied to the reactor protection system being developed in Korea to identify design weak points from a safety point of view.

In this paper, an improved direct torque control (DTC) method for sensorless matrix converter drives is proposed which enables to minimize torque ripple, to obtain unity input power factor, and to achieve good sensorless speed-control performance in the low speed operation, while maintaining constant switching frequency and fast torque dynamics. It is possible to combine the advantages of matrix converters with the advantages of the DTC strategy using space vector modulation and a flux deadbeat controller. To overcome the phase current distortion by the non-linearity of a matrix converter drive, the simple non-linearity compensation method using PQR power theory are presented in the proposed scheme. Experimental results are shown to illustrate the feasibility of the proposed strategy.

In this paper, we propose a switching control method for a class of 2nd order nonlinear systems with single input. The main idea is to switch the control law before the trajectory of the solution arrives at singular hyperplanes which are defined by the denominator of the control law. The proposed method can handle a class of nonlinear systems which is difficult to be stabilized by the existing methods such as feedback linearization, backstepping, control Lyapunov function, and sliding mode control.