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

Image-based control is one of robot control methods using a camera and it can control a robot indirectly by controlling only image information on an image plane without using the robot states. In this paper, an image-based trajectory tracking method is described for a nonholonomic mobile robot. Especially, a fuzzy controller is adopted to regard the robot speed, usually assumed to be constant, as time varying one. The controller was tested on simulation experiments. The results of the experiments show the usability of the designed fuzzy controller, giving the improvement of the control performance, such as the reduction of overshoot, the shortening of convergence time, etc. Additionally, the impact of control parameters on the robot behavior is proved in the simulations.

Image-based trajectory tracking with fuzzy control for nonholonomic mobile robots

It is known that the equation of motions for an omnidirectional mobile robot is nonlinear with respect to the rotational angle between the moving and absolute coordinate systems In this paper, a fuzzy model approach is applied to the control of a time-varying rotational angle, in which multiple linear models are obtained by utilizing the original nonlinear model in some representative angles and they are used to derive the optimal type 2 servo gain matrices The effectiveness of the proposed method is illustrated by giving some simulations for the trajectory tracking control problem

Rotational control of an omnidirectional mobile robot using a fuzzy servo controller

Autonomous Trajectory Planning of Mobile Robots Using an Evolution Strategy

In this paper, a back propagation neural network (NN) is presented for the inverse kinematics of redundant manipulator with joint limits. Since the inverse kinematics has infinite number of joint angle vectors, a fuzzy neural network (FNN) is designed to provide an approximate value for that vector. This vector is fed into the NN as a hint input vector to guide the output of the NN within the self-motion. This FNN is designed based on cooperatively controlled each joint angle in the sense that it stops the motion on the critical axis at its limit in the expense of more compensation from the most relaxed joint to accomplish the task. The joint velocity limits as well as the joint limits are incorporated in this method. Simulations are implemented based on four-link redundant manipulator to show the effectiveness of the proposed control system.

Cooperative fuzzy hint acquisition for avoiding joint limits of redundant manipulators

In industries manufacturing metallic molds, various NC machine tools are used. We have already proposed a desktop NC machine tool with compliance control capability to automatically cope with the finishing process of LED lens molds. The NC machine tool has the ability to control the polishing force acting between an abrasive tool and a work piece. The force control method is called impedance model force control. The most effective gain is the desired damping of the impedance model. Ideally, the desired damping is calculated from the critical damping condition after considering the effective stiffness in the force control system. However, there is a problem in that the effective stiffness of the NC machine tool has undesirable nonlinearity. The nonlinearity has a bad influence on the force control stability. In this article, a fine tuning method of the desired damping is considered using neural networks. The neural networks acquire the nonlinearity of effective stiffness. The promise is evaluated through an experiment.

Keigo Watanabe

Papers

Image-based trajectory tracking with fuzzy control for nonholonomic mobile robots

Rotational control of an omnidirectional mobile robot using a fuzzy servo controller

Autonomous Trajectory Planning of Mobile Robots Using an Evolution Strategy

Cooperative fuzzy hint acquisition for avoiding joint limits of redundant manipulators

CAD/CAM-based force controller using a neural network-based effective stiffness estimator