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Chen T.P.,Fortune Institute of Technology
Science and Technology of Welding and Joining | Year: 2010

The main purpose of this paper is to determine the optimum operating conditions of friction stir welding dissimilar metals joints, namely AA6061 aluminium alloy and SS400 low carbon steel. The optimum operation is the combination of four mainly controllable process parameters for the best quality of uncontrollable parameters, such as both interface and welded zone impact values. In this paper, the V-notch impact value represents the interface toughness and the C-notch impact value for welded zone toughness. Moreover, the possible failure type can be analysed by observing the fractured surface after impact test. The best bending toughness of dissimilar metals joints is produced by the combination of the tool rotation speed of 550 rev min-1, the transverse speed of 0•9 mm s-1, the tool tilting backward 2° angles, and the tool pin diameter of 6 mm. © 2010 Institute of Materials, Minerals and Mining.


Lin K.-J.,Fortune Institute of Technology
ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings | Year: 2011

This paper addresses the neural network (NN) based observer and adaptive control design for a class of singularly perturbed nonlinear (SPN) systems. Based on the Lyapunov stability theorem and the tool of linear matrix inequality (LMI), we solve observer and the controller gain matrix and a common positive-definite matrix and then a sufficient condition is derived to stabilize the SPN systems. The allowable perturbation bound can be determined via some algebra inequalities, such that the proposed neural network based observer and the adaptive control will stabilize the SPN systems for all ε ∈(0,ε). A practical system is given to illustrate the validity of the proposed scheme. © 2011 Asian Control Association.


An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research. © 2010 Elsevier Ltd.


Liao G.-C.,Fortune Institute of Technology
International Journal of Electrical Power and Energy Systems | Year: 2014

Air-conditioning load forecasting accuracy precludes high efficacy air-conditioning operation, and is also a key advantage in developing Smart Microgrid (SMG) power generating system control. The Wavelet Neural Network (WNN) was adopted as a principle element in air-conditioning load forecasting with Improved Differential Evolution Algorithm (IDEA) as an optimizing method for adjusting WNN parameters. This approach has replaced the formal feedback method used in solving network parameters. IDEA is an optimizing technique with simple calculation and fewer adjustable parameters, allowing the optimum solution for the entire system to be acquired more accurately and rapidly. After solving the optimum parameters WNN is further applied to accomplish air-conditioning load forecasting. A Fuzzy Expert System is adopted as an adjustment measure for special conditions, allowing ideal forecasting results to be reached. This study made practical comparisons among the generally applied methods for optimizing air-conditioning forecasting, such as the Artificial Neural Network (ANN), Evolutionary Programming-Artificial Neural Network (EP-ANN), Genetic Algorithm-Artificial Neural Network (GA-ANN), Ant Colony Optimization-Artificial Neural Network (ACO-ANN) and Particle Swarm Optimization-Artificial Neural Network (PSO-ANN), to prove the advantages and applicability of the proposed method. © 2014 Elsevier Ltd. All rights reserved.


Yen H.-C.,Fortune Institute of Technology
IEEE Transactions on Industrial Electronics | Year: 2010

This paper proposes a novel topology to drive the cold cathode fluorescent lamps (CCFLs) for liquid crystal displays (LCDs) in a direct-type backlight module. The topology is capable of driving an even number of lamps with identical current without additional balancing circuits, thereby significantly reducing the display's size, weight, and cost. Aiming at alleviating the influence of parasitic capacitance and thus balancing the lamp currents and light output, the proposed topology comprises series CCFLs and the secondary sides of transformers, takes the leakage inductances of the transformer and the parasitic capacitances of the metal back-plank as a resonance tank, and provides both ends of lamps the voltages of equal magnitude and opposite phase. A prototype of the multi-CCFLs driver is designed and built for a backlight module with 14 lamps in a 32-in LCD. Experimental results demonstrate the effectiveness and feasibility of the current balance topology. © 2010 IEEE.


Chen L.-S.,Fortune Institute of Technology
Library Collections, Acquisition and Technical Services | Year: 2010

This paper aims to integrate a library system so that it becomes intelligent. We use swarm intelligence to develop friendly human-computer interface software for readers using a personal or notebook computer. We program the system and software with Extensible Markup Language (XML) and C Sharp language. The kernel library automatically communicates with other libraries by agents, so readers can search from the closest library. This study adds only one component to the kernel library, and the other libraries do not add this component. They maintain their original status. Readers do not use a browser; they directly communicate with the library search system, saving much time. Readers without IT skills can also easily search for books in the library system. © 2009 Elsevier Ltd.


Lin K.-J.,Fortune Institute of Technology
Computers and Mathematics with Applications | Year: 2012

This paper addresses stabilizing a class of fuzzy control systems with a guaranteed H∞ control performance via a new descriptor system approach. Based on the sector nonlinearity concept of Tanaka and Wang (2001) [1], the uncertain nonlinear system can be exactly represented by T-S fuzzy models. Then, we propose using the composite state and output feedback (CSAOF) fuzzy control for the control design. A new descriptor fuzzy system will be represented in this paper. Based on the Lyapunov stability theorem and the linear matrix inequality (LMI) tool, we solve the controller gain matrices, some positive constants and some common positive-definite matrices. Then, we derive two sufficient conditions to stabilize the uncertain fuzzy control systems with guaranteed H∞ control performance. Moreover, the developed H∞ criterion guarantees that the influence of external disturbance is as small as possible. A practical system is given to illustrate the validity of the proposed scheme. © 2011 Elsevier Ltd. All rights reserved.


Lin K.-J.,Fortune Institute of Technology
International Journal of Systems Science | Year: 2013

This article addresses the neural network (NN)-based control and observer design for a class of singularly perturbed nonlinear (SPN) systems with guaranteed H ∞ control performance. We consider the problem of NN-based observer design for SPN systems with guaranteed H ∞ control performance. Based on the Lyapunov stability theorem and the tool of linear matrix inequality, we solve the controller and the observer gain matrices and some common positive-definite matrices. Then, two sufficient conditions were derived to stabilise the SPN systems. The allowable perturbation bound ε* can also be determined via some algebra inequalities, such that the proposed NN-based observer and the adaptive control will stabilise the SPN systems for all. A practical system is given to illustrate the validity of the proposed scheme. © 2013 Copyright Taylor and Francis Group, LLC.


Liao G.-C.,Fortune Institute of Technology
International Journal of Electrical Power and Energy Systems | Year: 2012

With the decreasing of the fossil fuel energy resources and the increasing energy load demand Distributed Generation (DG) technologies have received more attention Smart MicroGrid (SMG) systems integrate the power generation advantages from new and renewable energy power generation systems connected to the standard grid. SMG can enhance the comprehensively cascaded energy utilization and also provide an effective complementary network that improves power supply reliability and power quality. SMG has become one of the most up-to-date and important topics in the field of power systems all over the world. According to distributed generation SMG characteristics, such as Photo Voltaic (PV), Wind Power (WP), Water Turbine (WT), Fuel Cell (FC), gas turbine and micro-gas turbine, considering different fuel efficiency, operation and maintenance costs, the greenhouse gas emission levels of distributed generation with various types and capacity a novel SMG model environmental and economic dispatch is presented that considers generation cost and emission costs. This paper uses the quantum genetic algorithm to confirm the accuracy and validity of a mathematic model using actual examples compared with other optimization approaches used to solve the economic dispatch problem. The superiority and usability of the proposed approach is discussed. © 2012 Elsevier Ltd. All rights reserved.


Liao G.-C.,Fortune Institute of Technology
International Journal of Electrical Power and Energy Systems | Year: 2012

This paper presents a novel algorithm-Isolation Niche Immune Genetic Algorithm for solving power system Bid-Based Dynamic Economic Dispatch (INIGA-BDED). Economic Dispatch determines the electrical power to be generated by the committed generating units in a power system so that the generation cost can minimized, while simultaneously satisfying various load demands. The Bid-Based Dynamic Economic Dispatch model is proposed in order to maximize the social profit under a competitive electricity market environment. This model synthetically considers various constraints on ramp rates, transmission line capacity and emission constraints. The Isolation Niche Immune Genetic Algorithm was induced as a new solution for this model. With the introduction of niche technology, the immune genetic algorithm capability in dealing with multi-peak model function optimization was enhanced. This paper proposes the Niche based on the Isolation mechanism which is based on biological possesses. The proposed method effectively ensures diverse group solutions and also has a strong ability to guide evolution. Using the immune genetic algorithm itself is a very good and innovative method for multi-peak model function solutions. A new improved method for this algorithm is also presented in this paper. This research integrated these two methods to enhance the evolutionary capability in seeking a more optimal solution for solving nonlinear programming. The test results from this integrated method were very good. © 2012 Elsevier Ltd. All rights reserved.

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