There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

Robust Model-Based Fault Diagnosis for Dynamic Systems

비만아 부모의 돌봄 경험: q 방법론

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

This paper presents an effective force control method in which a fuzzy-neuro force controller is automatically adjusted in accordance with the unknown dynamics of an environment using a neural network. The adjustment strategy of the fuzzy-neural force controller, according to the environment dynamics, is automatically generated by the neural network in off-line manner using genetic algorithms with fuzzy evaluation. The effectiveness of the proposed force controller is evaluated by computer simulation with a 3-DOF planar robot manipulator model.

Generation of adjustment strategy of fuzzy-neural force controllers using genetic algorithms with fuzzy evaluation

In recent years, rapid deterioration of infrastructure equipment is regarded as a problem and the maintenance management of it is important for preventing serious accidents. Particularly, in a bridge like the Seto-Ohashi, it takes a long time to inspect the whole and it is also dangerous because of high-place work. Then, use of unmanned aerial vehicles (UAVs) can be considered as one of the alternative ways to the human visual-check. Among them, Quadrotors are attracting attention and they have excellent maneuverability and operability because they control the position and attitude of the airframe by changing the revolution velocity of four rotors. However, since a thrust cannot be generated except for upward direction, there is a weak point in which it is out of control, if it is affected by the influence of an ascending current etc. when hovering. In particular, vortices are generated around huge structures represented by bridges, so that it is difficult to inspect without considering this effect. In this research, it is aimed at developing a Quadrotor that can check infrastructures in harsh environments by attaching auxiliary thrusters and an anemometer. This paper first outlines a proposed Quadrotor. In addition, it verifies the accuracy of our own built-in anemometer. Finally, the effect of the airframe on the anemometer is verified through some experiments. The experimental results showed that the manufactured anemometer needs to be redesigned.

Development of an Anemometer to Assist a Quadrotor with Auxiliary Thrusters

A novel control algorithm for controlling underactuated robot manipulators using fuzzy based switching with an NN-compensator is presented. One fundamental feature of this approach is to employ elemental controllers in order to fulfill the ultimate control objective, without performing rigorous linearizations or any other augmentation methods to the original nonlinear system. Parameters of both antecedent and consequent parts of a fuzzy indexer and the compensator are optimized off-line by using evolutionary computation. Such parameters are trained for different initial configurations of the manipulator and the common rules can be brought into the online operation of underactuated manipulators. The effectiveness of the proposed method is demonstrated using a computer simulation.

NN-compensator with fuzzy based switching for controlling 3-DOF underactuated manipulator

Impact Sound Control of Robotic Manipulators

In this paper, an iterative curved surface fitting method using a small sliding window is first proposed to smooth the original organized point cloud data (PCD) with noise and fluctuation. Samples included in a small sliding window positioned in PCD are successively fitted to a quadratic surface from upper left to lower right using a least squares method. In the iterative process, outliers of samples are asymptotically removed based on an evaluation index. This proposed method allows original PCD to be smoothed keeping its own shape feature. Then, the already developed stereolithography (STL) generator is used to produce triangulated patches from the smoothed PCD. The process allows to reconstruct 3D digital data of a real object written with STL format for reverse engineering from original PCD with noise. The effectiveness and usefulness of the proposed curved surface fitting method are demonstrated through actual smoothing experiments.

Keigo Watanabe

Papers

Generation of adjustment strategy of fuzzy-neural force controllers using genetic algorithms with fuzzy evaluation

Development of an Anemometer to Assist a Quadrotor with Auxiliary Thrusters

NN-compensator with fuzzy based switching for controlling 3-DOF underactuated manipulator

Impact Sound Control of Robotic Manipulators

Iterative curved surface fitting algorithm using a raster-scanning window