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
6 results
Search Results
Item Minimum-phase criteria for sampled systems via symbolic approach(1996-12-13) C.-H. Wang; W.-Y. Wang; C.-C. HsuIn this paper, we propose a symbolic approach to determine the sampling-time range which guarantees minimum-phase behaviours for a sampled system with a zero-order hold. By using Maple, a symbolic manipulation package, the symbolic transfer function of the sampled system, which contains sampling time T as an independent variable, can be easily obtained. We then adopt the critical stability constraints to determine the sampling-time range which ensures that the sampled system has only stable zeros. In comparison with existing methods, the approach proposed in this paper has less restrictions on the continuous plant and is very easy to implement in any symbolic manipulation packages. Several examples are illustrated to show the effectiveness of this approachItem DSP-based fuzzy neural networks and its application in speech recognition(1999-10-15) S.-C. Chen; C.-C. Hsu; W.-Y. WangA fuzzy-neural network needs to be trained through a learning process, so that suitable membership functions and weightings can be obtained. However, most neural networks are only simulated by computer software, which are not practical for real applications. It is therefore our objective to design an integrated circuit system based on a DSP processor with powerful arithmetical capabilities and fast data processing, and relevant peripheral devices to implement the fuzzy neural network. In terms of implementation cost and feasibility for practical applications, this DSP-based fuzzy neural network will be more practical and usable. Finally, a prospective application of the DSP processor-based fuzzy neural network to recognize speech from a non-designated person is proposedItem Discrete modeling of continuous interval using high-order integrators(1999-06-04) C.-C. Hsu; W.-Y. WangA higher-order integrator approach is proposed to obtain an approximate discrete-time transfer function for uncertain continuous systems having interval uncertainties. Thanks to simple algebraic operations of this approach, the resulting discrete model is a rational function of the uncertain parameters. The problem of non-linearly coupled coefficients of exponential nature in the exact discrete-time transfer function is therefore circumvented. Furthermore, interval structure of the uncertain continuous-time system is preserved in the resulting discrete model by using this approach. Formulas to obtain the lower and upper bounds for the discrete interval system are derived, so that existing robust results in the discrete-time domain can be easily applied to the discretized system. Digital simulation and design for the continuous-time interval plant can then be performed based on the obtained discrete-time interval modelItem Impact of sampling time on tustin digitization(ACTA Press, 1996-01-01) C.-H. Wang; W.-Y. Wang; C.-C. HsuThis paper investigates the impact of sampling time on Tustin digitization. A Q-matrix representation for the digitized system via Tustin transformation is first proposed. It is shown that Tustin transformation is a special case of the higher-order integrator approaches to digitize a continuous system. Pole-variation loci is then introduced to describe the trajectories of poles of the digitized system using Tustin transformation when sampling time is varied from zero to infinity. With new theorems derived in this paper, the pole-variation loci can be easily sketched. Sampling time of any point on the pole-variation loci of the digitized system can be determined by the angle of the vector drawn from the origin to the designated pole location. System dynamics of the digitized system can then be estimated from the sampling time, which determines the pole locations.Item Minimum-phase criteria for sampled systems via symbolic approach(Taylor & Francis, 1997-01-01) C.-H. Wang; W.-Y. Wang; C.-C. HsuIn this paper, we propose a symbolic approach to determine the sampling-time range which guarantees minimum-phase behaviours for a sampled system with a zero-order hold. By using Maple, a symbolic manipulation package, the symbolic transfer function of the sampled system, which contains sampling time T as an independent variable, can be easily obtained. We then adopt the critical stability constraints to determine the sampling-time range which ensures that the sampled system has only stable zeros. In comparison with existing methods, the proposed approach in this note has less restrictions on the continuous plant and is very easy to implement in any symbolic manipulation package. Several examples are illustrated to show the effectiveness of this approach.Item Approximationransform using higher order integrators and its applications in sampled-data control systems(Taylor & Francis, 1998-01-01) C.-H. Wang; C.-C. Hsu; W.-Y. WangIn this paper, we first clarify the difference between the approximate z transform and the discrete equivalent of a continuous system using higher-order integrators. It is shown that a 1/ ts factor needs to be included for the approximate z transform but not for the discrete equivalent. We further apply the approximate z transform to facilitate the stability analysis of sampled-data control systems, with or without uncertain parameters, ft is shown in this paper that the approximate z transform greatly simplifies the stability analysis of a sampled-data control system, which is regarded as rather difficult ( if not impossible) to handle because of its transcendental nature. The results can be easily obtained and show reasonably good approximations with this approach. Several examples are used to illustrate the effectiveness of this new method.