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Chen C.-S.,Da - Yeh University
IEEE Transactions on Fuzzy Systems | Year: 2011

This paper proposes a robust self-organizing neural-fuzzy-control (RSONFC) scheme for a class of uncertain nonlinear multiple-input-multiple-output (MIMO) systems. We first develop a self-organizing neural-fuzzy network (SONFN) with concurrent structure and parameter learning. The fuzzy rules of SONFN are generated or pruned systematically. The proposed RSONFC scheme comprises an SONFN identifier, an uncertainty observer, and a supervisory controller. The SONFN identifier functions as the principal controller, and the uncertainty observer is designed to oversee uncertainties within the compound system. The supervisory controller combines sliding-mode control (SMC) and an adaptive bound-estimation scheme with various weights to achieve H∞ tracking performance with a desired level of attenuation. Projection-type adaptation laws of network parameters developed using the Lyapunovs synthesis approach guarantee the stability of the overall control system. Simulation studies on a single-link flexible-joint manipulator and a two-link robot demonstrate the effectiveness of the proposed control scheme. © 2006 IEEE. Source


Tsai H.-L.,Da - Yeh University
Solar Energy | Year: 2010

This paper presents a novel model of photovoltaic (PV) module which is implemented and analyzed using Matlab/Simulink software package. Taking the effect of sunlight irradiance on the cell temperature, the proposed model takes ambient temperature as reference input and uses the solar insolation as a unique varying parameter. The cell temperature is then explicitly affected by the sunlight intensity. The output current and power characteristics are simulated and analyzed using the proposed PV model. The model verification has been confirmed through an experimental measurement. The impact of solar irradiation on cell temperature makes the output characteristic more practical. In addition, the insolation-oriented PV model enables the dynamics of PV power system to be analyzed and optimized more easily by applying the environmental parameters of ambient temperature and solar irradiance. © 2010 Elsevier Ltd. All rights reserved. Source


Lin C.-T.,Da - Yeh University
Online Information Review | Year: 2010

Purpose - For the internet to realise its full marketing potential, travel agencies need a well-designed e-travel site. Yet the attributes that affect customers' perceptions leading to acceptance of e-travel sites are still unclear. This study seeks to focus on why users accept or reject e-travel sites and how users' acceptance is affected by three widely recognised features of sites - relevant information content, information quality, and functionality needs service. Design/methodology/approach - The study analysed a survey of 242 users of Taiwanese e-travel sites to test the hypothesised expanded technology acceptance model. Findings - The empirical results indicate that the information content, information quality and functionality service of e-travel sites strongly determine the perceived ease of use. Relevant information content and information quality also strongly determine perceived usefulness, which in turn leads to the behavioural intention to use e-travel sites. Originality/value - The findings of the study suggest that web site information must be sufficiently provided, quickly expanded and constantly updated to maintain correct and current content to meet users' information needs as well as an appropriate assistance function to provide good levels of web-based customer service. These attributes should satisfy visitors, making them likely to revisit e-travel sites. © Emerald Group Publishing Limited. Source


Tsaur W.-J.,Da - Yeh University
Expert Systems with Applications | Year: 2012

The mobile agent plays an increasingly important role in electronic business applications, because it can provide the essential properties of personalization, automation and intelligence, etc. This paper proposes several appropriate security schemes for protecting mobile agent networks in electronic business applications. As far as mobile agent security is concerned, we develop a proxy signature scheme for protecting mobile agents against malicious agent hosts. The proposed proxy signature scheme can protect users' private keys stored in smart cards, and provide the fairness of contracts signed by agents. In addition, we also design a proxy authenticated encryption scheme so that the signature of the contracts will satisfy users' constraints, and the non-repudiation of servers can be achieved. On the other hand, as far as agent host security is concerned, we apply the idea of proxy signature to construct an authentication scheme for protecting agent hosts. This scheme is to achieve the requirements of authentication and authorization. Furthermore, we also implement the proposed security schemes to achieve security requirements of confidentiality, integrity, authenticity, and non-repudiation for protecting Linux-based mobile agents and hosts in an electronic auction application. Hence, we affirm that the proposed security schemes are suitable for practical electronic business applications in mobile-agent-based network environments. © 2011 Elsevier Ltd. All rights reserved. Source


Chen C.-S.,Da - Yeh University
IEEE Transactions on Power Electronics | Year: 2010

In this paper, a TakagiSugenoKang-type self-organizing recurrent-neural- fuzzy network (T-SORNFN) is proposed for the trajectory tracking control of linear microstepping motor (LMSM) drives. Without a priori knowledge, the T-SORNFN is constructed to model the inverse dynamics of a LMSM drive by a set of recurrent fuzzy rules built online through concurrent structure and parameter learning. The fuzzy rules in the T-SORNFN can be either generated or eliminated to obtain a suitable-sized network structure, and a recursive recurrent learning laws of network parameters are derived based on the supervised gradient-descent method to achieve fast-learning converge. Based on the Lyapunov stability approach, the convergence of the T-SORNFN is guaranteed by choosing varied learning rates. Furthermore, an inverse-control architecture that incorporates T-SORNFN and a proportionalderivative controller is used to control the LMSM drive in a changing environment. A recursive least-squares (RLS) algorithm is utilized for online fine-tuning the consequent parameters in T-SORNFN to obtain a more precision model. Simulated and experimental results of a LMSM drive are provided to verify the effectiveness of the proposed T-SORNFN control system, and its superiority is validated in comparison with NFN and RNFN control systems. © 2010 IEEE. Source

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