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。
News
Browse
11 results
Search Results
Item A merged-fuzzy-neural network and its application in fuzzy-neural control(2006-10-11) I-H. Li; W.-Y. Wang; S.-F. Su; M.-C. ChenThis paper proposes an observer-based adaptive fuzzy-neural controller, structured by a merged fuzzy-neural network (merged-FNN) to reduce the number of adjustable parameters. In this paper, the merged-FNN is proved to take the place of the traditional fuzzy-neural networks under some assumptions. Moreover, the overall adaptive schemes using the proposed merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. From experimental examples, the proposed merged-FNN has far fewer parameters than the traditional FNN, and the computation time is significantly reduced. To demonstrate the effectiveness of the proposed methods, simulation results are illustrated in this paper.Item Intelligent Control for Anti-lock Braking Systems to Track Dynamic Optimal Slip Ratio(2007-01-01) W.-Y. Wang; I-H. Li; D.-F. Chung; M.-C. ChenItem Dynamic Slip Ratio Estimation and Control of Antilock Braking Systems Considering Wheel Angular Velocity(2007-10-10) M.-C. Chen; W.-Y. Wang; I-H. Li; S.-F. SuThis paper proposes an antilock braking system (ABS), in which unknown road characteristics are resolved by a road estimator. This estimator is based on the LuGre friction model with a road condition parameter, and can transmit a reference slip ratio to a slip ratio controller through a mapping function considering the effect of wheel angular velocity. In the controller design, a direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed. Finally, this paper gives simulation results of an ABS with the road estimator and the DAFC, and shows good effectiveness under varying road conditions.Item A Practical Nighttime Vehicle Distance Alarm System(2008-10-15) M.-C. Lu; C.-P. Tsai; W.-Y. Wang; M.-C. Chen; C.-C. Hsu; Y. Y. LuThis paper presents a practical nighttime vehicle distance measuring method based on a single CCD image. The method combines an image-based distance measuring system. To solve the nighttime feature extraction problem, the proposed method uses two taillights as the feature. Based on the proportionality of similar triangles, distance between a CCD camera and the taillights of the vehicle ahead can be measured. The method focuses on detecting the taillights and differentiating the targeted vehicle from others on the basis of partial image analysis instead of whole image processing. The system is both fast and simple. The accuracy of the proposed method is demonstrated in this paper through experiences.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 Fuzzy measure based mobile robot controller for autonomous movement control(2011-06-10) G.-Y. Pan; C.-P. Tsai; M.-C. Chen; W.-Y. Wang; C.-R. TsaiThis paper proposes a novel fuzzy measure based mobile robot controller design method. We apply this method in a simulation where the movement of a mobile robot along a wall is governed by this controller. The ultrasonic range finder sensors onboard the mobile robot are used to measure the distance between the robot and the wall. The measurement results are recorded as fuzzy measure inputs and the results of the fuzzy measure are used to control the movement of the mobile robot along the wall. Our simulations compare the movements of the mobile robot with and without the fuzzy measure controller. The simulation results show that the mobile robot using the fuzzy measure controller exhibits a more controlled movement behavior than that using a controller without fuzzy measure.Item Dynamic slip ratio estimation and control of antilock braking systems using an observer-based direct adaptive fuzzy-neural controller(IEEE Industrial Electronics Society, 2009-05-01) W.-Y. Wang; I-H. Li; M.-C. Chen; S.-F. Su; S.-B. HsuThis paper proposes an antilock braking system (ABS), in which unknown road characteristics are resolved by a road estimator. This estimator is based on the LuGre friction model with a road condition parameter and can transmit a reference slip ratio to a slip-ratio controller through a mapping function. The slip-ratio controller is used to maintain the slip ratio of the wheel at the reference values for various road surfaces. In the controller design, an observer-based direct adaptive fuzzy–neural controller (DAFC) for an ABS is developed to online-tune the weighting factors of the controller under the assumption that only the wheel slip ratio is available. Finally, this paper gives simulation results of an ABS with the road estimator and the DAFC, which are shown to provide good effectiveness under varying road conditionsItem A New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems(ICIC International, 2010-03-01) W.-Y. Wang; I-H. Li; M.-C. Chen; S.-F. Su; Y.-G. LeuThis paper proposes an observer-based adaptive controller with a merged fuzzy-neural network for nonaffine nonlinear systems under the constraint that only the system output is available for measurement. Using a conventional fuzzy-neural network leads to rule explosion which leads to huge computation time. Our proposed merged-FNN does not have this problem, and can take the place of the conventional fuzzy-neural networks under some assumptions while maintaining the property of stability. Moreover, the adaptive scheme using the merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. Finally, this paper gives examples of the proposed controller for nonaffine nonlinear systems, and is shown to provide good effectiveness.Item Robust T–S Fuzzy-Neural Control of Uncertain Active Suspension Systems(International Journal of Fuzzy Systems, 2010-12-01) M.-C. Chen; W.-Y. Wang; S.-F. Su; Y.-H. Chien