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 A GA-based indirect adaptive fuzzy-neural controller for uncertain nonlinear systems(2002-12-06) W.-Y. Wang; C.-C. Hsu; C.-W. Tao; Y.-H. LiIn this paper, a novel approach to adjust both the control points of B-spline membership functions (BMFs) and the weightings of fuzzy-neural networks using a reduced-form genetic algorithm (RGA) is proposed. Chromosomes consisting of both the control points of BMFs and the weightings of fuzzy-neural networks are coded as an adjustable vector with real number components and searched by the RGA. Moreover, we propose an application of the RGA in designing an RGA-based indirect adaptive fuzzy-neural controller (RIAFC) for uncertain nonlinear dynamical systems. The free parameters of the indirect adaptive fuzzy-neural controller can successfully be tuned on-line via the RGA approach. A supervisory controller is incorporated into the RIAFC to stabilize the closed-loop nonlinear system. An example of a nonlinear system controlled by RIAFC are demonstrated to show the effectiveness of the proposed method.Item Sliding Control for Linear Uncertain Systems(2003-09-19) C.-W. Tao; M.-L. Chan; W.-Y. WangA new design approach to enhance a terminal sliding mode controller for linear systems with mismatched time-varying uncertainties is presented in this paper. The nonlinear sliding surface is used to have the system states arrive at the equilibrium point in the finite time period. The sliding coefficient matching condition is extended for the terminal sliding mode control. The uncertain system with the proposed terminal sliding mode controller is shown to be invariant on the sliding surface. The reaching mode of the sliding surface is guaranteed and the close-loop system is stable. Moreover, the undesired chattering is alleviated with the designed terminal sliding mode controller. Simulation results are included to illustrate the effectiveness of the presented terminal sliding mode controller.Item Robust control of the mismatched systems with the fuzzy integral sliding controller(2003-10-08) C.-W. Tao; M.-L. Chan; W.-Y. WangAn adaptive fuzzy integral sliding mode controller for mismatched time-varying linear systems is presented in this paper. The proposed fuzzy integral sliding mode controller is designed to have zero steady state system error under step inputs and alleviate the undesired chattering around the sliding surface. The parameters in the fuzzy mechanism are adapted on-line to improve the performance of the fuzzy integral sliding mode control system. Thus, the bounds of the uncertainties are not required to be known in advance. The designed fuzzy integral sliding mode control system is shown to be invariant on the sliding surface. Moreover, the reaching mode of the sliding surface is guaranteed and the close-loop system is stable. Simulation results are included to illustrate the effectiveness of the presented fuzzy integral sliding mode controller.Item Fuzzy-neural function approximation using a vector evaluation genetic algorithm(2003-01-01) W.-Y. Wang; C.-C. Hsu; C.-W. Tao; Y.-H. LiItem 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 Gene boundary adjustment of reduced-form genetic algorithms for B-spline neural network training(2004-01-01) W.-Y. Wang; C.-W. Tao; C.-Y. Kuo; C.-Y. ChuItem Design of sliding mode controllers for bilinear systems with time varying uncertainties(IEEE Systems, Man, and Cybernetics Society, 2004-02-01) C.-W. Tao; W.-Y. Wang; M.-L. ChanSliding mode controllers for the bilinear systems with time varying uncertainties are developed in this paper. The bilinear coefficient matching condition which is similar to the traditional matching condition for linear system is defined for the homogeneous bilinear systems. It can be seen that the bilinear coefficient matching condition is very limited and is not generally applicable to the nonhomogeneous bilinear system. Thus, the sliding coefficient matching condition is also considered for the bilinear systems with time varying uncertainties. Then, the sufficient conditions are provided for the reaching mode of the time varying uncertain bilinear systems to be guaranteed by the designed sliding mode controllers. Moreover, the stability of the uncertain bilinear systems with the sliding mode controller is discussed. Simulation results are included to illustrate the effectiveness of the proposed sliding mode controllers.Item Adaptive bound reduced-form genetic algorithms for B-spline neural network training(IEICE, 2004-11-01) W.-Y. Wang; C.-W. Tao; C.-G. ChangIn this paper, an adaptive bound reduced-form genetic algorithm (ABRGA) to tune the control points of B-spline neural networks is proposed. It is developed not only to search for the optimal control points but also to adaptively tune the bounds of the control points of the B-spline neural networks by enlarging the search space of the control points. To improve the searching speed of the reduced-form genetic algorithm (RGA), the ABRGA is derived, in which better bounds of control points of B-spline neural networks are determined and paralleled with the optimal control points searched. It is shown that better efficiency is obtained if the bounds of control points are adjusted properly for the RGA-based B-spline neural networks.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 Identification of Four Types of High-Order Discrete-Time Nonlinear Systems Using Hopfield Neural Networks(Watam Press, 2007-01-01) W.-Y. Wang; I-H. Li; S.-F. Su; C.-W. Tao