Browsing by Author "Chen, Chun-Yao"

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Analysis and Design of Indirect Adaptive Fuzzy Controller for Nonlinear Hysteretic Systems
(2015-03-01)
Wang, Chi-Hsu
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Wang, Jyun-Hong
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Chen, Chun-Yao
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
In order to handle the nonlinear properties of hysteretic systems, an indirect adaptive fuzzy controller (IAFC) is proposed in this paper. However, it is hard to directly identify the unknown hysteretic effects. Therefore, to overcome this problem, a dynamic hysteretic equation is employed and modified to construct the nonlinear properties of backlash-like hysteretic systems. Besides, the existence of an IAFC can be derived in this paper. Compared with the existing fuzzy control methods, our proposed IAFC is simpler and can handle the more general hysteretic problems with our new learning algorithm. Based on the learning algorithm, the adaptive and the control laws not only can be derived but the stability of the closed-loop system can also be guaranteed by the Lyapunov stability criterion. Finally, the proposed IAFC is compared to the adaptive backstepping control method, and the results show that our proposed IAFC can effectively handle the nonlinear properties in the backlash-like hysteretic systems.
Design of Indirect Adaptive Fuzzy Control (IAFC) for Nonlinear Hysteretic Systems
(2014-01-01)
Wang, Chi-Hsu
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Wang, Jyun-Hong
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Chen, Chun-Yao
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
Nonlinear hysteretic phenomena occur in many physical systems, such as electronic throttle and solenoid valves in automobiles, piezoelectric sensors, and many other mechanical actuators. In order to handle the nonlinear properties of hysteretic systems, an indirect adaptive fuzzy controller (IAFC) is proposed in this paper. However, it is a hard task to directly identify unknown hysteretic effects. Firstly, to overcome this problem, a hysteretic function is employed to construct the nonlinear properties of backlashlike hysteretic systems. Then the existence of an indirect adaptive controller (IAFC) is derived in this paper. Unlike the existing fuzzy control methods, our proposed IAFC can deal with different kinds of hysteretic problems with adaptive and control laws. Based on the learning algorithm, the adaptive and control laws not only can be derived but the stability of the closed- loop system can also be guaranteed by the Lyapunov stability criterion. Finally, MATLAB software is used for simulations, and the results show that our proposed IAFC can effectively handle the nonlinear properties in some unknown hysteretic systems.
High-performance poly(2,3-diphenyl-1,4-phenylene vinylene)-based polymer light-emitting diodes by blade coating method
(2011-08-03)
Liao, Yung-Ming
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Shih, Hung-Min
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Hsu, Kuang-Hui
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Hsu, Chain-Shu
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Chao, Yu-Chiang
A new series of super high brightness and luminance efficient poly(2,3-diphenyl-1,4-phenylene vinylene) (DP-PPV)-based electroluminescent (EL) polymers containing methoxy or long branched alkoxy chains were synthesized via Gilch polymerization. The branched alkoxy groups were introduced to enhance solubility for blade and spin-coating processes. Monomers of DMeO-PPV and m-Ph-PPV were used to increase steric hindrance and prevent close packing of the main chain. By controlling the feeding ratio of different monomers during polymerization, DP-PPV derivatives with high molecular weight were obtained. All synthesized polymers possess high glass transition temperatures and thermal stabilities. The maximum photoluminescent emissions of the thin films are located between 544 and 547 nm. Cyclic voltammetry analysis reveals that the band gaps of these light-emitting materials are in the range of 2.75 -2.84 eV. Blade coating was used to fabricate multilayer polymer light-emitting diodes. A multilayer electroluminescent device with the configuration of ITO/PEDOT:PSS/TFB/P1/TPBi/LiF/Al exhibited a very high luminescence efficiency (10.96 cd A(-1)). The maximum brightness of the multilayer EL device ITO/PEDOT:PSS/TFB/P3/CsF/Al reached up to 78,050 cd m(-2) with a low turn-on voltage (4.0 V). For further investigation, polymer P3 was blended with DPPFBNA to achieve white light-emitting device; the multilayer devices generated a maximum brightness of 1085 cd m(-2) and a luminance efficiency of 0.75 cd A(-1), with CIE coordinates (0.28, 0.33) at 11 V. (C) 2011 Elsevier Ltd. All rights reserved.
Intelligent Chaos Synchronization of Fractional Order Systems via Mean-Based Slide Mode Controller
(2015-06-01)
Wang, Chi-Hsu
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Chen, Chun-Yao
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電機工程學系
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Department of Electrical and Computer Engineering
In this paper, a new mean-based adaptive fuzzy neural network sliding mode control is developed to perform the chaos synchronization among the master-slave fractional order uncertain systems. The mean-based expansion is adopted to replace the traditional Taylor expansion to transform a nonlinear function into a partially linear form for the linearization of nonlinear systems. In comparison with the traditional Taylor method, the proposed mean-based method can estimate the first-order derivative term on the identifier model, which will somehow alleviate the computational burden. Based on the learning algorithms, the adaptive laws and control laws can be tuned on-line to synchronize the master-slave fractional order uncertain systems. Furthermore, the stability of the closed-loop system can not only be assured but the synchronization deviation of external perturbation can also be alleviated. Finally, simulation examples are illustrated to demonstrate the feasibility and the synchronization performance of this new approach.
Intelligent Missile Guidance by Using Adaptive Recurrent Neural Networks
(2014)
Wang, Chi-Hsu
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Chen, Chun-Yao
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交大名義發表
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電機工程學系
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National Chiao Tung University
In this paper, an adaptive recurrent neural network (RNN) controller is proposed for missile guidance. We address the problem of one agent (defending missiles) and one target (incoming missiles) in air battle scenario. The RNN controller is designed to force an agent (or defending missile) toward a target (or incoming missile), and a monitoring controller is also designed to reduce the error between the RNN controller and ideal one. The former is the main controller that can be easily designed. Its weighting factors are activated to dispatch the agent toward the target. By using the Lyapunov constraints, we update the weighting factors for the proposed RNN controller to guarantee the stability of the path evolution (or planning) system. Excellent simulation results are obtained by using this new approach for missile guidance, which show that our RNN has the lowest average miss distance (MD) among the several techniques.
Multi-layer organic light-emitting diodes processed from solution using phosphorescent dendrimers in a polymer host
(2010-06-01)
Ko, Li-Chun
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Liu, Tsung-Yu
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Chen, Chun-Yao
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Yeh, Chung-Ling
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Tseng, Shin-Rong
A uniform dispersion of highly soluble phosphorescent dendrimer emitters is achieved by blending with a polymer host poly(9-vinylcarbazole) (PVK) containing N,N'-diphenyl-N, N'-(bis(3-methylphenyl)-[1,1-biphenyl]-4,4'-diamine (TPD) and 2-(4-biphen-4'-yl)-5-(4-tert-butylphenyl)-1,3,4-oxadiazole (PBD). No visible aggregation or self-quenching was observed for guest-to-host weight ratios of up to 33:67. The dendrimers contain a fac-tris(2-phenylpyridyl)iridium(III) [Ir(ppy)(3)] core, first generation biphenyl-based dendrons, and 2-ethylhexyloxy surface groups. The guest-host blend is used for all solution processed organic light-emitting diodes. A maximum external and current efficiency of 10.2% and 38 cd/A (at 5 V and a brightness of 50 cd/m(2)), and a maximum brightness of 27,000 cd/m(2) (at 14.5 V), were obtained when a CsF/Al cathode was used. Blade coating was used to fabricate a multi-layer structure that also contained an electron-transport layer. The device that had a LiF/Al cathode had a maximal efficiency of 40 cd/A corresponding to an external quantum efficiency of 10.8% (at 5 V and a brightness of 19 cd/m(2)). The maximum brightness of the second device was 17,840 cd/m(2) at 14 V. (C) 2010 Elsevier B.V. All rights reserved.
Toward a New Task Assignment and Path Evolution (TAPE) for Missile Defense System (MDS) Using Intelligent Adaptive SOM with Recurrent Neural Networks (RNNs)
(2015-06-01)
Wang, Chi-Hsu
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Chen, Chun-Yao
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Hung, Kun-Neng
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
In this paper, a new adaptive self-organizing map (SOM) with recurrent neural network (RNN) controller is proposed for task assignment and path evolution of missile defense system (MDS). We address the problem of N agents (defending missiles) and D targets (incoming missiles) in MDS. A new RNN controller is designed to force an agent (or defending missile) toward a target (or incoming missile), and a monitoring controller is also designed to reduce the error between RNN controller and ideal controller. A new SOM with RNN controller is then designed to dispatch agents to their corresponding targets by minimizing total damaging cost. This is actually an important application of the multiagent system. The SOM with RNN controller is the main controller. After task assignment, the weighting factors of our new SOM with RNN controller are activated to dispatch the agents toward their corresponding targets. Using the Lyapunov constraints, the weighting factors for the proposed SOM with RNN controller are updated to guarantee the stability of the path evolution (or planning) system. Excellent simulations are obtained using this new approach for MDS, which show that our RNN has the lowest average miss distance among the several techniques.