Hwa Hsia University of Technology

About: Hwa Hsia University of Technology is a education organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Control theory & Nonlinear system. The organization has 477 authors who have published 822 publications receiving 9486 citations.

CANN: An intrusion detection system based on combining cluster centers and nearest neighbors

Abstract: The aim of an intrusion detection systems (IDS) is to detect various types of malicious network traffic and computer usage, which cannot be detected by a conventional firewall. Many IDS have been developed based on machine learning techniques. Specifically, advanced detection approaches created by combining or integrating multiple learning techniques have shown better detection performance than general single learning techniques. The feature representation method is an important pattern classifier that facilitates correct classifications, however, there have been very few related studies focusing how to extract more representative features for normal connections and effective detection of attacks. This paper proposes a novel feature representation approach, namely the cluster center and nearest neighbor (CANN) approach. In this approach, two distances are measured and summed, the first one based on the distance between each data sample and its cluster center, and the second distance is between the data and its nearest neighbor in the same cluster. Then, this new and one-dimensional distance based feature is used to represent each data sample for intrusion detection by a k-Nearest Neighbor (k-NN) classifier. The experimental results based on the KDD-Cup 99 dataset show that the CANN classifier not only performs better than or similar to k-NN and support vector machines trained and tested by the original feature representation in terms of classification accuracy, detection rates, and false alarms. I also provides high computational efficiency for the time of classifier training and testing (i.e., detection).

Study of Reconfiguration for the Distribution System With Distributed Generators

Abstract: This paper proposes a reconfiguration methodology based on an Ant Colony Algorithm (ACA) that aims at achieving the minimum power loss and increment load balance factor of radial distribution networks with distributed generators. A 33-bus distribution system and a Tai-Power 11.4-kV distribution system were selected for optimizing the configuration and to demonstrate the effectiveness of the proposed methodology for solving the optimal switching operation of distribution systems. The simulation results have shown that lower system loss and better load balancing will be attained at a distribution system with distributed generation (DG) compared to a system without DG. Furthermore, the simulation results also satisfy and suitability reference merits of the proposal method.

Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems

Abstract: In this paper, an observer-based direct adaptive fuzzy-neural control scheme is presented for nonaffine nonlinear systems in the presence of unknown structure of nonlinearities. A direct adaptive fuzzy-neural controller and a class of generalized nonlinear systems, which are called nonaffine nonlinear systems, are instead of the indirect one and affine nonlinear systems given by Leu et al. By using implicit function theorem and Taylor series expansion, the observer-based control law and the weight update law of the fuzzy-neural controller are derived for the nonaffine nonlinear systems. Based on strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. Moreover, the overall adaptive scheme guarantees that all signals involved are bounded and the output of the closed-loop system will asymptotically track the desired output trajectory. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.

Adaptive fuzzy terminal sliding mode controller for linear systems with mismatched time-varying uncertainties

Abstract: A new design approach of an adaptive fuzzy terminal sliding mode controller for linear systems with mismatched time-varying uncertainties is presented in this paper. A fuzzy terminal sliding mode controller is designed to retain the advantages of the terminal sliding mode controller and to reduce the chattering occurred with the terminal sliding mode controller. The sufficient condition is provided for the uncertain system to be invariant on the sliding surface. The parameters of the output fuzzy sets in the fuzzy mechanism are adapted on-line to improve the performance of the fuzzy sliding mode control system. The bounds of the uncertainties are not required to be known in advance for the presented adaptive fuzzy sliding mode controller. The stability of the fuzzy control system is also guaranteed. Moreover, the chattering around the sliding surface in the sliding mode control can be reduced by the proposed design approach. Simulation results are included to illustrate the effectiveness of the proposed adaptive fuzzy terminal sliding mode controller.