電機工程學系
Permanent URI for this communityhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/85
歷史沿革
本系成立宗旨在整合電子、電機、資訊、控制等多學門之工程技術，以培養跨領域具系統整合能力之電機電子科技人才為目標，同時配合產業界需求、支援國家重點科技發展，以「系統晶片」、「多媒體與通訊」、與「智慧型控制與機器人」等三大領域為核心發展方向，期望藉由學術創新引領產業發展，全力培養能直接投入電機電子產業之高級技術人才，厚植本國科技產業之競爭實力。
本系肇始於民國92年籌設之「應用電子科技研究所」，經一年籌劃，於民國93年8月正式成立，開始招收碩士班研究生，以培養具備理論、實務能力之高階電機電子科技人才為目標。民國96年8月「應用電子科技學系」成立，招收學士班學生，同時間，系所合一為「應用電子科技學系」。民國103年8月更名為「電機工程學系」，民國107年電機工程學系博士班成立，完備從大學部到博士班之學制規模，進一步擴展與深化本系的教學與研究能量。
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Item Real-Time Tracking of Human Body Based on Discrete Wavelet Transform(2007-01-19) Shyang-Li Chang; Chen-Chien Hsu; Tsung-Chi Lu; Ti-Ho WangA novel human body tracking system based on discrete wavelet transform is proposed in this paper based on color and spatial information. The configuration of the proposed tracking system is very simple, consisting of a CCD camera mounted on a rotary platform for tracking moving objects. By using the position information of objects in the image frame captured by the camera, the rotary platform is controlled to position the tracking object around the central area of images to improve tracking efficiency. Thanks to the use of discrete wavelet transform, computations can be significantly reduced while achieving real-time tracking.Item Suitability of Redesigned Digital Control Systems Having an Interval Plant via an Evolutionary Approach(American Society of Mechanical Engineers, 2011-04-01) Chen-Chien Hsu; Tsung-Chi LuIn this paper, a quantitative index is proposed to address the performance evaluation and design issues in the digital redesign of continuous-time interval systems. From the perspective of signal energy, a worst-case energy resemblance index (WERI), defined as the ratio of the worst-case continuous signal energy (WCSE) of the continuous-time interval system over the worst-case discrete sequence energy (WDSE) of the redesigned digital system, is established for evaluating the closeness of the system performance between the redesigned digital control system and its continuous-time counterpart. Based on the WERI, performance of the redesigned digital systems can be evaluated for different discretization methods at different sampling times. It is found that no discretization method outperforms the others for all sampling times. Because of serious nonlinearities and nonconvexity involved, the determination of WCSE and WDSE is first formulated as an optimization problem and subsequently solved via an evolutionary algorithm. To guarantee stability of the redesigned digital system, the largest sampling time allowed is also evolutionarily determined to establish a sampling-time constraint under which robust Schur stability of the redesigned digital system can be ensured. For design purposes, sampling time required can be determined according to the user-specified WERI, which serves as a performance specification for fine tuning the performance of the redesigned digital control system.Item Minimum-Phase Criterion on Sampling Time for Sampled-Data Interval Systems Using Genetic Algorithms(Elsevier, 2008-09-01) Chen-Chien Hsu; Tsung-Chi LuIn this paper, a genetic algorithm-based approach is proposed to determine a desired sampling-time range which guarantees minimum phase behaviour for the sampled-data system of an interval plant preceded by a zero-order hold (ZOH). Based on a worst-case analysis, the identification problem of the sampling-time range is first formulated as an optimization problem, which is subsequently solved under a GA-based framework incorporating two genetic algorithms. The first genetic algorithm searches both the uncertain plant parameters and sampling time to dynamically reduce the search range for locating the desired sampling-time boundaries based on verification results from the second genetic algorithm. As a result, the desired sampling-time range ensuring minimum phase behaviour of the sampled-data interval system can be evolutionarily obtained. Because of the time-consuming process that genetic algorithms generally exhibit, particularly the problem nature which requires undertaking a large number of evolution cycles, parallel computation for the proposed genetic algorithm is therefore proposed to accelerate the derivation process. Illustrated examples in this paper have demonstrated that the proposed GA-based approach is capable of accurately locating the boundaries of the desired sampling-time range.Item Discrete Modelling of Continuous-Time Systems Having Interval Uncertainties Using Genetic Algorithms(Institute of Electronics, Information and Communication Engineers, 2008-01-01) Chen-Chien Hsu; Tsung-Chi Lu; Heng-Chou ChenIn this paper, an evolutionary approach is proposed to obtain a discrete-time state-space interval model for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete interval model is first formulated as multiple mono-objective optimization problems for matrix-value functions associated with the discrete system matrices, and subsequently optimized via a proposed genetic algorithm (GA) to obtain the lower and upper bounds of the entries in the system matrices. To show the effectiveness of the proposed approach, roots clustering of the characteristic equation of the obtained discrete interval model is illustrated for comparison with those obtained via existing methods.Item Real-Time Tracking of Human Body Based on Discrete Wavelet Transform(World Scientific and Engineering Academy and Society (WSEAS), 2007-05-01) Chen-Chien Hsu; Tsung-Chi Lu; Ti-Ho Wang