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 describes the design and analysis of a biologically inspired central pattern generator (CPG) using a network of mutually coupled nonlinear oscillators to generate rhythmic walking pattern for biped robots The paper examines the characteristics of a CPG model composed of a network of nonlinear oscillators, and the effect of assigning symmetrical and asymmetrical coupling mechanism among oscillators within the network structure under different possibilities of inhibitions and excitations The paper highlights the necessity to understand the targeted physical system and its functionalities before concluding the design parameters of the CPG In addition, the paper considers the way in which the sensory feedback contributes to generate adaptive walking trajectory and enhance gait stability, and how the driving input and external perturbation affect the speed of locomotion and change the period of its own active phase Modeling of bipedal robot using a CPG based controller and a musculo-skeletal system has been achieved for the purpose to realize the interaction with each other and to study the necessary conditions for stable dynamic walking on dynamic terrain that lead to stable and sustained response from the network The kinematics and dynamics of a five-link biped robot has been modeled and its joints are actuated through simulation by the proportional torques output from the CPG to generate the trajectories for hip, knee, and ankle joints The CPG based bipedal locomotion is carried out and evaluated through simulations using MATLAB

Bipedal Locomotion Control via CPGs with Coupled Nonlinear Oscillators

In this paper, a defect detection method using deep convolutional neural network (DCNN), support vector machine (SVM) and template matching techniques is introduced. First, a DCNN for visual inspection is designed and trained using a large number of images to inspect undesirable defects such as crack, burr, protrusion, chipping, spot and fracture phenomena which appear in the manufacturing process of resin molded articles. Then the trained DCNN named sssNet and well-known AlexNet are, respectively, incorporated with two SVMs to classify sample images with high recognition rate into accept as OK category or reject as NG one, in which compressed feature vectors obtained from the DCNNs are used as inputs for the SVMs. The performances of the two types of SVMs with the DCNNs are compared and evaluated through training and classification experiments. Finally, a template matching technique is further proposed to efficiently extract important target areas from original training and test images. This will be able to enhance the reliability and accuracy for defect detection.

Defect detection method using deep convolutional neural network, support vector machine and template matching techniques

It is known that a behavior-based control approach is effective for acquiring an intelligent control system of robots. However, further improvements are required for making any behavior-based control system robust against changes in the environments. A module learning method has been applied in the framework of fuzzy behavior-based control to have an adaptive behavioral fusion. In this paper, an adaptive fusion strategy is proposed to adaptively select a cooperative fusion unit or competitive fusion unit, depending on the external sensor information. Some simulations are given to illustrate that the present control systems are flexible against the change of environments or untrained environments, compared to those with a conventional priority-based fusion unit.

A Fuzzy Behavior-Based Control for Mobile Robots Using Adaptive Fusion Units

A Discrete-Time Adaptive Filter for Stochastic Distributed Parameter Systems

A novel concept for designing a fuzzy logic-based switching controller to control underactuated manipulators is presented. The proposed controller employs elemental controllers, which are designed in advance. Parameters of both antecedent and consequent parts of a fuzzy indexer are optimized by using evolutionary computation. Design parameters of the fuzzy indexer are encoded into chromosomes, i.e., the shapes of the Gaussian membership functions and corresponding switching laws of the consequent part are evolved to minimize the angular position errors. Then, these trained fuzzy rules can be brought into the online operation of underactuated manipulators. Simulation results show that the new methodology is effective in designing controllers for underactuated robot manipulators.

Keigo Watanabe

Papers

Bipedal Locomotion Control via CPGs with Coupled Nonlinear Oscillators

Defect detection method using deep convolutional neural network, support vector machine and template matching techniques

A Fuzzy Behavior-Based Control for Mobile Robots Using Adaptive Fusion Units

A Discrete-Time Adaptive Filter for Stochastic Distributed Parameter Systems

Control of three degrees-of-freedom underactuated manipulator using fuzzy based switching