Catálogo de publicaciones - libros

Most electronic chassis control systems so far have been designed for optimization of its own performance. This, sometimes, has resulted in performance degradation when two or more control modules were operating together. Recently, great R&D effort is being given to judicious integration of individual chassis control systems in an effort to further enhance the overall vehicle performance. The vehicle system equipped AFS and ESC is a multi-input-multi-output(MIMO) system. In this paper, chassis controller using Characteristic Locus(CL) design method based on frequency-domain techniques was developed for integrating AFS(Active Front Steering) with ESC(Electronic Stability Control) systems. Finally, the proposed controller is varified with CarSim simulation in various driving condition.

This paper presents the velocity estimation of a mobile robot using a regular polygonal array of optical flow sensors that are installed at the bottom of a mobile robot. First, the basic principle of the proposed localization scheme is described, which is motivated from the changing optical flow sensor readings according to the mobile robot traveling pattern. Second, the velocity kinematic mapping from a mobile robot to an array of optical flow sensors is derived as an overdetermined linear system. Third, for a given set of optical flow sensor readings, the mobile robot velocity is estimated based on the least squares solution to the derived system. Finally, simulation results are given to demonstrate the validity of the proposed velocity estimation.

Aiming at the characteristics of permanent magnet synchronous motor (PMSM) such as strong coupling and nonlinearity, we propose a fractional-order control scheme for the speed control of PMSM system based on the analysis of the fractional calculus theory. The simulation is conducted by using Matlab / Simulink. Simulation results indicate that the fractional-order PI controller can improve the disturbance rejection performance of the PMSM speed-adjusting system.

A traditional fuzzy control system the Max-Min CRI (Compositional Rule of Inference) method, which equivalently combines rules for an inference, for fuzzy inference suffers from a critical problem. It produces a big error for a premise which is very similar or identical to one of premises in rules. It is because the importance of rules is not taken into the consideration for inference. In this paper, we propose a novel fuzzy inference method to reduce the error by providing weights to composition of rules according to the similarity of premises. In the experimental section, we show that the proposed similarity measure can reduce a lot of error regions compared with the conventional Max-Min CRI method using the example of D.C. series motor controller.

In this paper, the distribution of the shortest linear recurring sequence over the ring is studied, it is found that the amount of sequences whose length is n can be calculated and the recurring distribution regulation of the shortest linear recurring sequences is proposed. The possibility of finding the non-recurring distribution of the shortest linear recurring length of some special sequences over the ring is also discussed which can be used in the further research work.

In 2005, Kim and Choi showed that PAP-based RADIUS protocol is vulnerable to a man-in-the-middle attack by using Casper and CSP/FDR model checking tool, and an improved protocol is presented that can withstand the attack. The current paper, however, demonstrates that Kim-Choi’s improved protocol is still vulnerable to an off-line password guessing attack and password extracting attack. We also present an improvement to the protocol, in order to isolate such problems.

Whether constant (i.e., pi) is normal is a confusing problem without any strict theoretical demonstration except for some statistical proof. A new concept of pi series is introduced to seek for the possible quasi-chaotic characteristics of pi by the studies of the basic elements such as power spectral density, phase space construction, maximal Lyapunov exponents and correlation dimension in the field of nonlinear time series. In this paper, we propose a new image encryption algorithm with position diffusion and pixel confusion based on pi series. After this algorithm is applied to a still image, the encrypted image demonstrates strong resistance towards exterior attacks such as statistical attacks and differential attacks.

There exist specific characteristics in TFT-LCD industry, such as unexpected demand fluctuation, customized products that each customer will designate a specific key component, long lead time of procurement and short product life cycle. This research presents a Genetic Algorithm & Neural Network model for monthly sales forecasting of TFT-LCD products in Taiwan. The practical situation and its requirements are explained and two system approaches are discussed: a) a neural network for supervised learning of the functional behavior of time series data and its approximation, and b) a Genetic Algorithm system for modeling a systems behavior with the possibility of exploiting expert information and systematic optimization. Advantages and disadvantages of both concepts are described with emphasis placed on the structural development of the Genetic Algorithm system. Both systems have been tested and satisfying results are shown with practical data.

Synthetic test is regarded as a very important method for testing the breaking capability of high voltage circuit breakers, in order to ensure its equivalence property the high voltage circuit and the arc prolonging circuit must be injected accurately between 200~500μs before the aero of the short circuit current zero. However it is difficult to prediction the current zero under the unsymmetrical conditions. In this paper an approach of time series prediction of short circuit current is presented. By delay coordinate embedding, the zero of the short circuit current is predicted with high accuracy. As a result, the high voltage circuit and the arc prolonging circuit may be injected in good time. And the simulation and the practical application results show a good agreement with the predications.

As conversation system it must converse with various users and have to talk about various conversations, so we have to prepare large numbers of information for conversation knowledge database, but it is so especially difficult for us. The wealth of information on the web is full and quick so those make it an attractive resource for seeking quick information to simple. Recognizing a human’s emotional state can be helpful in various contexts. The most promising one is probably the man-machine interaction, the communication between an assisting robot in the household and its human user. In this paper we present an experiment named an emotion recognition conversation system based on knowledge database automatic architecture. In this exploration there are two parts different than the generic conversation system. First, our conversation system can automatic construct of knowledge database base on the Really Simple Syndication parse. Second, this system can recognize emotion from the conversation contents. The experiment showed that this method could achieve better results in practice.