Recently, high throughput screening for microorganisms with desired characteristics from a large heterogeneous population has become possible. Single cell separation has taken on increasing significance in recent years, and several different methods have been proposed so far. In this paper, we introduce several cell manipulation methods aiming at single cell separation and investigation. At first, methods for the separation of microorganisms are classified. Then, we introduce two different approaches, that is, (1) indirect manipulation using laser trapped microtools and (2) thermal gelation.

This paper addresses the issue of position control of a chain of multiple mass-spring-damper (CMMSD) units which can be found in many physical systems. The dynamic model of a CMMSD system with any degrees of freedom is expressed in a closed-form for the convenience of the controller design. Backstepping and model reference adaptive control (MRAC) approaches are then used to develop two adaptive output feedback controllers to control the position of a CMMSD system. The proposed controllers rely on the measurements of the input (force) and the output (position of the mass unit at the end of the chain) of the system without the knowledge of its parameters and internal states. Simulations are used to verify the effectiveness of the controllers

The unmanned tandem helicopter, which is a MIMO nonlinear system with complexity and inherent instability, exists in unstable zero dynamics. In this paper, approximate linearization is presented to design the controller for output tracking of an unmanned tandem helicopter based on the dynamic augment method, and the simulation results are encouraging.

RAIM techniques based on TLS have rarely been addressed because TLS requires a great number of computations. In this paper, the particular form of the observation matrix H, is exploited so as to develop a new TLS-based sequential algorithm to identify an errant satellite. The algorithm allows us to enjoy the advantages of TLS with less computational burden. The proposed algorithm is verified through a numerical simulation.

An autonomous navigation algorithm for marine vehicles is proposed in this paper using fuzzy logic under COLREG guidelines. The VFF (Virtual Force Field) method, which is widely used in the field of mobile robotics, is modified for application to the autonomous navigation of marine vehicles. This Modified Virtual Force Field (MVFF) method can be used in either track-keeping or collision avoidance modes. Moreover, the operator can select a track-keeping pattern mode in the proposed algorithm. The collision avoidance algorithm has the ability to handle static and/or moving obstacles. The fuzzy expert rules are designed deliberately under COLREG guidelines. An extensive simulation study is used to verify the proposed method.

This paper presents a design method of delay-dependent control for T-S fuzzy systems with time delays. Based on parallel distributed compensation (PDC) and a descriptor model transformation of the system, a delay-dependent control is utilized. An appropriate Lyapunov-Krasovskii functional is chosen for delay-dependent stability analysis. A sufficient condition for delay-dependent control is represented in terms of linear matrix inequalities (LMIs).

In this paper, we introduce a new soft computing technique that dwells on the ideas of combining fuzzy rules in a fuzzy system with polynomial neural networks (PNN). The PNN is a flexible neural architecture whose structure is developed through the modeling process. Unfortunately, the PNN has a fatal drawback in that it cannot be constructed for nonlinear systems with only a small amount of input variables. To overcome this limitation in the conventional PNN, we employed one of three principal soft computing components such as a fuzzy system. As such, a space of input variables is partitioned into several subspaces by the fuzzy system and these subspaces are utilized as new input variables to the PNN architecture. The proposed soft computing technique is achieved by merging the fuzzy system and the PNN into one unified framework. As a result, we can find a workable synergistic environment and the main characteristics of the two modeling techniques are harmonized. Thus, the proposed method alleviates the problems of PNN while providing superb performance. Identification results of the three-input nonlinear static function and nonlinear system with two inputs will be demonstrated to demonstrate the performance of the proposed approach.

Counters for the various kinds of banknotes require high-speed distinctive point extraction and recognition. In this paper we propose a new point extraction and recognition algorithm for Euro banknotes. For distinctive point extraction we use a coordinate data extraction method from specific parts of a banknote representing the same color. To recognize banknotes, we trained 5 neural networks. One is used for inserting direction and the others are used for face value. The algorithm is designed to minimize recognition time by using a minimal amount of recognition data. The simulated results show a high recognition rate and a low training period. The proposed method can be applied to high speed banknote counting machines.

This paper presents the development of a knowledge-based control system operating via the Internet. With the synergy provided by the Internet, the central expert controller with its knowledge-base has the potential to serve a multitude of front-end clients located anywhere in the world provided they have Internet access. In this way, the operational span of the knowledge-based control system can be expanded to virtually anyplace within the reach of the Internet. This configuration has positive implications in improving the efficiency of distributed operations, thereby enabling plantwide optimization and costs savings. Datasocket technology is adopted to facilitate a more efficient data exchange between the knowledge-based central server and the front-end clients. A specific application in the remote monitoring and fault diagnosis of machines using the proposed control configuration is presented in the paper.

This paper describes the design and implementation techniques of a generic Internet-based telerobotic system. The purpose is to make available the precious technical information and hands-on experience of the authors for the research community. The paper is based on the telerobotics system that the authors recently implemented between KAIST, Korea and Saga University, Japan. In its current functionality, two control modes: high-level supervisory control and low-level supervisory control are explored demonstrating their merits and demerits.

This paper provides a motion analysis of soft-fingertip object manipulation tasks by presenting a dynamic model of multi-fingered object manipulations with soft fingertips. It is fundamentally observed that soft fingertips employed in a multi-fingered hand generate some deformation effects during the manipulation process and also that those effects are closely related to the behavior of the manipulated object. In order to analyze the motion of using soft fingertips, a dynamic manipulation control scheme is presented. Simulation and experimental results demonstrate the motion of soft-fingertips applied in object manipulating tasks and are further used to discuss the characteristics of soft-fingertip motions.

In displaying a virtual wall using a passive haptic device equipped with passive actuators such as electric brakes, unsmooth motion frequently occurs. This undesirable behavior is attributed to time delay due to slowness in the virtual environment update and force approximation due to the inability of a brake to generate torque in arbitrary directions. In this paper a new control scheme called direct control is proposed to achieve smooth display on the wall-following task with a passive haptic device. In direct control, brakes are controlled so that the normal component of a resultant force at the end-effector vanishes, based on the force analysis at the end-effector of the passive haptic device using the passive FME (Force Manipulability Ellipsoid). Various experiments have been conducted to verify the validity of the direct control scheme with a 2-link passive haptic system.

The majority of real-world problems encountered by engineers involve simultaneous optimization of competing objectives. In this case instead of single optima, there is a set of alternative trade-offs, generally known as Pareto-optimal solutions. The use of evolutionary algorithms Pareto GA, which was first introduced by Goldberg in 1989, has now become a sort of standard in solving Multiobjective Optimization Problems (MOPs). Though this approach was further developed leading to numerous applications, these applications are based on Pareto ranking and employ the use of the fitness sharing function to maintain diversity. Another scheme for solving MOPs has been presented by J. Nash to solve MOPs originated from Game Theory and Economics. Sefrioui introduced the Nash Genetic Algorithm in 1998. This approach combines genetic algorithms with Nash's idea. Another central achievement of Game Theory is the introduction of an Evolutionary Stable Strategy, introduced by Maynard Smith in 1982. In this paper, we will try to find ESS as a solution of MOPs using our game model based co-evolutionary algorithm. First, we will investigate the validity of our co-evolutionary approach to solve MOPs. That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP. Second, we will evaluate the effectiveness of our approach, comparing it with other methods through rigorous experiments on several MOPs.

Conventionally, profile non-uniformity has been characterized by relying on approximated profile with angle or anisotropy. In this study, a new non-uniformity model for etch profile is presented by applying a discrete wavelet to the image obtained from a scanning electron microscopy (SEM). Prediction models for wavelet-transformed data are then constructed using a back-propagation neural network. The proposed method was applied to the data collected from the etching of tungsten material. Additionally, 7 experiments were conducted to obtain test data. Model performance was evaluated in terms of the average prediction accuracy (APA) and the best prediction accuracy (BPA). To take into account randomness in initial weights, two hundred models were generated for a given set of training factors. Behaviors of the APA and BPA were investigated as a function of training factors, including training tolerance, hidden neuron, initial weight distribution, and two slopes for bipolar sig-moid and linear function. For all variations in training factors, the APA was not consistent with the BPA. The prediction accuracy was optimized using three approaches, the best model based approach, the average model based approach and the combined model based approach. Despite the largest APA of the first approach, its BPA was smallest compared to the other two approaches.