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Item Design of a K-band Low Insertion Loss Variation Phase Shifter Using 0.18- μm CMOS Process(2010-12-10) Chung-Han Wu; Wei-Tsung Li; Jeng-Han Tsai; Tian-Wei HuangThis paper demonstrates a k-band low insertion loss variation phase shifter with over 330° continuously phase tuning range from 21-25GHz in standard 0.18-μm CMOS technology. This phase shifter is composed of a 180° continuously phase tuning range reflection type phase shifter (RTPS) and a 180° discrete switch type phase shifter (STPS). The measured phase shift range is 336° with low loss variation of 1.3dB at 22GHz and the maximum insertion loss is 16 dB at 22GHz. To the best of authors' knowledge, the MMIC is the lowest insertion loss variation phase shifter in CMOS technology at 22GHz.Item CMOS oversampling ΔΣ magnetic-to-digital converters(IEEE Solid-State Circuits Society, 2001-10-01) Chien-Hung Kuo; Shr-Lung Chen; Lee-An Ho; Shen-Iuan LiuIn this paper, two CMOS oversampling delta-sigma (ΔΣ) magnetic-to-digital converters (MDCs) are proposed. The first MDC consists of the magnetic operational amplifier (MOP) and a first-order switched-capacitor (SC) ΔΣ modulator. The second one directly uses the MOP to realize a first-order SC ΔΣ modulator. They can convert the external magnetic field into digital form. Both circuits were fabricated in a 0.5-μm CMOS double-poly double-metal (DPDM) process and operated at a 5-V supply voltage and the nominal sampling rate of 2.5 MHz. The dynamic ranges of these converters are at least ±100 mT. The gain errors within ±100 mT are less than 3% and the minimum detectable magnetic field can reach as small as 1 mT. The resolutions are 100 μT for both of the two MDCs. The measured sensitivities are 1.327 mv/mT and 0.45 mv/mT for the first and the second MDC, respectivelyItem 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 A Neural Network Based Context-Aware Handoff Algorithm for Multimedia Computing(Association for Computing Machinery (ACM), 2008-08-01) Tsungnan Lin; Chiapin Wang; Po-Chiang LinThe access of multimedia computing in wireless networks is concerned with the performance of handoff because of the irretrievable property of real-time data delivery. To lessen throughput degradation incurred by unnecessary handoffs or handoff latencies leading to media disruption perceived by users, this paper presents a link quality based handoff algorithm. Neural networks are used to learn the cross-layer correlation between the link quality estimator such as packet success rate and the corresponding context metric indictors, for example, the transmitting packet length, received signal strength, and signal to noise ratio. Based on a pre-processed learning of link quality profile, neural networks make essential handoff decisions efficiently with the evaluations of link quality instead of the comparisons between relative signal strength. The experiment and simulation results show that the proposed algorithm improves the user perceived qualities in a transmission scenario of VoIP applications by minimizing both the number of lost packets and unnecessary handoffs.Item MIMO Robust Control via T-S Fuzzy Models for Nonaffine Nonlinear Systems(2007-07-26) W.-Y. Wang; L.-C. Chien; I-H. Li; S.-F. SuThis paper proposes on-line modeling via Takagi-Sugeno (T-S) fuzzy models and robust adaptive control for a class of generalized multiple input multiple output (MIMO) nonlinear dynamic systems with external disturbances. The T-S fuzzy model is established to approximate the nonaffine nonlinear dynamic system in a linearized way and is used to be an error compensator for external disturbances and system uncertainly, i.e. the unmodeled dynamics, modeling errors and external disturbances. In second type adaptive laws, fuzzy B-spline membership functions (BMFs) are developed for on-line tuning. In this paper, we can prove that the closed-loop system which is controlled by the proposed controller is stable and the tracking error will converge to zero.Item 全天候深度影像辨識之履帶自走(2012-06-17) 方乃弘; 曾建凱; 李宜勳; 王偉彥Item Genetic algorithms-derived digital integrators and their applications in discretization of continuous systems(2002-01-01) C.-C. Hsu; W.-Y. Wang; C.-Y. YuA set of enhanced digital integrators (EDI) with improved accuracy via genetic algorithms are proposed in this paper. By specifying a desired power for the integrator to be sought and the interval for comparison, chromosomes consisting of parameters of the enhanced digital integrator are then searched by the genetic algorithm based on root mean squared (RMS) error between the original integrator and candidates of the enhanced digital integrator. Thus, all the best parameters of an optimal enhanced digital integrator can be evolutionarily obtained. To demonstrate the effectiveness of the proposed approach, the derived enhanced digital integrators are used to obtain the discrete approximation for continuous systems.Item A dynamic hierarchical fuzzy neural network for a general continuous function(2008-06-06) W.-Y. Wang; I-H. Li; S.-C. Li; M.-S. Tsai; S.-F. SuA serious problem limiting the applicability of the fuzzy neural networks is the "curse of dimensionality", especially for general continuous functions. A way to deal with this problem is to construct a dynamic hierarchical fuzzy neural network. In this paper, we propose a two-stage genetic algorithm to intelligently construct the dynamic hierarchical fuzzy neural network (HFNN) based on the merged-FNN for general continuous functions. First, we use a genetic algorithm which is popular for flowshop scheduling problems (GAFSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GAFSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.Item Design of hybrid sliding mode fuzzy PI controller(2005-10-01) 鄧聖山; 王偉彥Item 夜視型自主式群組校園巡邏機器人之研究--總計畫：夜視型自主式群組校園巡邏機器人之研究(行政院國家科學委員會, 2011-07-31) 王偉彥本整合型計畫的最終目標是讓群組機器人，能夠自主的在日間(一般CCD 辨識技術)、夜間或是光 線不佳(整合紅外線熱像儀影像辨識技術)的環境下，進行巡邏任務。子計畫二將以派屈網路理論，開 發夜間群組巡邏機器人之網路通訊、決策機制並以模糊派屈網路控制巡邏機器人之單機以實現分散式 網路控制概念。此外子計畫一將研發專屬群組機器人的資料庫、訊息整合系統與3D 使用者介面，建 立機器人估測電池電量及電池健康度之演算法。子計畫三將著重於發展未知環境之探索技術，藉各類 感測元件達到自主探索環境，完成機器人巡邏任務之環境地圖、地標標示與路徑規畫。子計畫四將利 用熱影像攝影發展非接觸式生物識別模組，另一方面，將根據熱影像攝影發展意外偵測模組(包含火災 識別模組與姿態模組)，此為使用熱影像式攝影機進行生物識別的附加價值。子計畫五使用熱影像攝影 技術使得機器人在巡視校園時，可以不受任何光線的影響，皆能清楚地偵測估算出環境中的行人與行 人的行徑方向和速度及相對位置。最後本整合型計畫將完成各項功能開發研究，以提高機器人在學界 和業界的實用性。