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 MIMO Robust Control via Adaptive T-S Merged Fuzzy Models for Nonaffine Nonlinear Systems(2007-01-01) W.-Y. Wang; Y.-H. Chien; I-H. Li; T.-T. LeeItem Adaptive T-S fuzzy controller for a class of general nonlinear systems(2006-01-01) W.-Y. Wang; Y.-H. Chien; I-H. LiItem T-S Fuzzy-Neural Control for Robot Manipulators(2008-08-25) W.-Y. Wang; Y.-H. Chien; Y.-G. Leu; Z.-H. Lee; T.-T. LeeThis paper proposes a novel method of on-line modeling and control through the Takagi-Sugeno (T-S) fuzzy-neural model for a class of general n-link robot manipulators. Compared with the previous method, the main contribution of this paper is an investigation of the more general robot systems using on-line adaptive T-S fuzzy-neural controller. Specifically, the general robot systems are exactly formed a linearized system via the mean value theorem, and then the T-S fuzzy-neural model can approximate the linearized system. Also, we propose an on-line identification algorithm and put significant emphasis on robust tracking controller design using an adaptive scheme for the robot systems. Finally, an example including two cases is provided to demonstrate feasibility and robustness of the proposed method.Item Control of Uncertain Active Suspension System with Antilock Braking system Using Fuzzy Neural Controller(2009-10-14) W.-Y. Wang; M.-C. Chen; Y.-H. Chien; T.-T. LeeThis paper proposes anti-lock braking system to integrate with active suspensions system applied in a quarter vehicles model, and can use a road estimate to get the road condition. This estimate is based on the LuGre friction model with a road condition parameter, and can transmit a reference slip ration to slip ratio controller through a mapping function considering the effect of road characteristics. In the controller design, an observer-based direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed. After, this paper will discuss that active suspension system influence on ABS. Active suspension systems are not ideal, unchanging, and certain, as many control systems assume. If parts of the suspension system fail, it becomes an uncertain system. In such cases, we need an approximator to remodel this uncertain system to maintain good control. We propose a new method to on-line identify the uncertain active suspension system and design a T-S fuzzy-neural controller to control it. Finally, integrating algorithm is constructed to coordinate these two subsystems. Simulation results of the ABS with active suspension system, and is shown to provide good effectiveness under varying conditions.Item On-Line Adaptive T-S Fuzzy Neural Control for Active Suspension Systems(2009-08-24) W.-Y. Wang; M.-C. Chen; Y.-H. Chien; T.-T. LeeVehicles are not always driven on smooth roads. If parts of the suspension system fail, it becomes an uncertain system. Thus we need an approximator to remodel this uncertain system to maintain good control. In this paper, we propose a new method to on-line identify the uncertain suspension system and design a T-S fuzzy-neural controller to control it. We first use the mean value theorem to transform the active suspension system into a virtual linearized system. In addition, an on-line adaptive T-S fuzzy-neural modeling approach to the design of robust tracking controllers is developed for the uncertain active suspension system. Finally, this paper gives simulation results of an uncertain suspension system with the on-line adaptive T-S fuzzy-neural controller, and is shown to provide good effectiveness under the conditions that parts of the suspension system fail.Item An Image-Based Area Measurement System(2011-06-10) C.-T. Chuang; C.-P. Tsai; M.-C. Lu; W.-Y. Wang; Y.-H. ChienA novel image-based area measurement system is proposed in this paper, we can convert the pixels of object into real area by image processes. No matter the system is vertical to the measuring plane or not and the height of system, it could calculates arbitrary two points on the image convert into the actual distance. This paper proposed a new structure for achieve our goal, there are four laser projects and camera fixed on same base, then generate four laser spots on the object or measurement plant, and assume connect each two laser spots as parallel lines, finally it could simulated a ruler in the image. Without consider photography angle for this system, it can measure area of floor or height of building.Item Design and Implementation of FPGA-Based Landslide Detection and Real-Time Monitoring System(2011-11-27) C.-P. Tsai; W.-Y. Wang; M.-C. Lu; Y.-H. Chien; S.-F. SuItem Design of Adaptive T-S Fuzzy-Neural Controller for a Class of Robot Manipulators Using Projection Update Laws(2010-10-13) Y.-H. Chien; W.-Y. Wang; T.-T. LeeAn on-line tracking controller design based on using T-S fuzzy-neural modeling for a class of general robot manipulators is investigated in this paper. Also, we use rojection update laws to tune adjustable parameters for preventing parameters drift. In addition, stability of the closed-loop systems is proven by using strictly-positive-real (SPR) Lyapunov theory. The proposed overall scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system asymptotically track the desired output trajectories. Finally, an example including two cases confirms the effectiveness of the proposed method.Item B-Spline Backstepping Control with Mean-Value Estimation and First-Order Filters(2011-11-27) Y.-H. Chien; W.-Y. Wang; Y.-G. Leu; K.-Y. Lian; T.-T. LeeItem Resarch and Design of Control System for a Tracked Robot with a Kinect Sensor(2012-07-02) N.-H. Fang; I-H. Li; W.-Y. Wang; L.-W. Lee; Y.-H. ChienThe paper displays a tracked robot that is capable of moving on pavement of any types. With Kinect’s in-depth info, the tracked robot can recognize pavement of any special kinds such as a ramp. In this paper, we use the example "recognizing a ramp and climbing it on an unknown pavement" to confirm the way to control a tracked robot. Four modes, a searching mode, a aligning mode, a closing mode and a climbing mode, are proposed to achieve the goal. Intelligent Fuzzy Controller is used here to reduce the cost of computing, increasing efficiency and have an ideal controlling effect.