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 Stable anti-lock braking system using output-feedback direct adaptive fuzzy neural control(2003-10-08) W.-Y. Wang; G.-M. Chen; C.-W. TaoIn this paper, an output feedback direct adaptive fuzzy neural controller for an anti-lock braking system (ABS) is developed. It is assumed that only the system output and the wheel slip ratio, is available for measurement. The main control strategy is to force the wheel slip ratio tracking variant optimal slip ratios, which may vary with the environment and assumed to be known during the vehicle-stopping period. By using the strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. To demonstrate the effectiveness of the proposed method, simulation results are illustrated.Item Robust sliding mode-like fuzzy logic control of anti-lock braking system(2003-03-14) W.-Y. Wang; K.-C. Hsu; G.-M. Chen在本篇論文中，為了控制防鎖死煞車系統，我們提出一個具強健特性的類滑動模式的模糊邏輯控制器，該控制器並擁有自行調整死區參數的功能。我們主要的控制策略在於迫使滑差追蹤並維持在最佳值0.2。考慮包含於汽車煞車系統中不確定因子的影響，本文所提出之控制器的表現仍具穩定性及可信賴性。我們並以防鎖死煞車系統模擬為例，來證明該控制器的正確性及有效性。Item Robust sliding mode-like fuzzy logic control for anti-lock braking systems with uncertainties and disturbances(2003-11-05) W.-Y. Wang; K.-C. Hsu; T.-T. Lee; G.-M. ChenIn this paper, we propose a robust sliding mode-like fuzzy logic controller for an anti-lock brake system (ABS) with self-tuning of the dead-zone parameters. The main control strategy is to force the wheel slip ratio tracking the optimum value 0.2. The proposed controller for anti-lock braking systems provides a stable and reliable performance under the uncertainties in vehicle brake systems. Simulation results will show the validity and effectiveness of the proposed sliding mode-like fuzzy logic controller.Item On-line genetic fuzzy-neural sliding mode controller design(2005-10-12) P.-Z. Lin; W.-Y. Wang; T.-T. Lee; G.-M. ChenIn this paper, a novel online B-spline membership function (BMF) fuzzy-neural sliding mode controller trained by an adaptive bound reduced-form genetic algorithm (ABRGA) is developed to guarantee robust stability and tracking performance for robot manipulators with uncertainties and external disturbances. The general sliding manifold is used to construct the sliding surface and reduce the chattering of the control signal, which can be nonlinear or time varying. For the purpose of identification, the proposed BMF fuzzy-neural network trained by the ABRGA approximates the regressor of the manipulator. An adaptive bound algorithm is used to aid and speed up the searching speed of the RGA. Simulation results show that the proposed on-line ABRGA-based BMF fuzzy-neural sliding mode controller is effective and yields superior tracking performance for robot manipulators.Item Fuzzy Control Using Intuitive Image Analysis(2008-05-27) G.-M. Chen; P.-Z. Lin; W.-Y. Wang; T.-T. Lee; C.-H. WangIn this paper, a novel fuzzy control scheme using intuitive image analysis is developed to imitate the intuitive human control behavior determined through human eyes. A CCD camera is used to gather the images of the controlled plant, and a simple algorithm is proposed to analyze the images. Unlike that in the visual servo control systems, the image information is utilized in a more intuitive way via the proposed image analysis algorithm. The difference between a reference image and the current image is numerically expressed and directly used by a fuzzy control system using a human-like control law. To investigate the effectiveness of the proposed fuzzy control scheme, it is applied to an inverted pendulum system. Simulation results show that the proposed scheme can achieve favorable tracking performance without prior knowledge of the controlled plant.Item Observer-Based Direct Adaptive Fuzzy-Neural Control for Anti-lock Braking Systems(中華民國模糊學會, 2006-12-01) G.-M. Chen; W.-Y. Wang; T.-T. Lee; C.-W. TaoIn this paper, an observer-based direct adaptive fuzzy-neural controller (ODAFNC) for an anti-lock braking system (ABS) is developed under the constraint that only the system output, i.e., the wheel slip ratio, is measurable. The main control strategy is to force the wheel slip ratio to well track the optimal value, which may vary with the environment. The observer-based output feedback control law and update law for on-line tuning of the weighting factors of the direct adaptive fuzzy-neural controller are derived. By using the strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be guaranteed. Simulation results demonstrate the effectiveness of the proposed control scheme forABS control.Item Image-based fuzzy control system(Institution of Engineering and Technology, 2008-03-27) G.-M. Chen; P.-Z. Lin; W.-Y. Wang; T.-T. Lee; C.-H WangA novel image-based fuzzy control (IBFC) scheme is developed to imitate the way humans use visual information to control objects. A CCD camera gathers images of the controlled plant, and a simple algorithm analyses the images. The proposed image analysis algorithm utilises image information more intuitively than visual servo control systems. The difference between a reference image and the current image is numerically expressed and directly used by a fuzzy control system using a human-like control law. To investigate the effectiveness of the proposed IBFC scheme, it is applied to control an inverted pendulum system. Simulation results show that the IBFC system can achieve favourable tracking performance without prior knowledge of the controlled plant.