Browsing by Author "Chu, SY"

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Cycloadditions of 16-electron 1,3-dipoles with ethylene. A density functional and CCSD(T) study
(1999-09-03)
Su, MD
;
Liao, HL
;
Chung, WS
;
Chu, SY
;
應用化學系
The 1,3-dipolar cycloaddition (DC) reactions of ethylene with nitrile ylide (CNC), nitrile imine (CNN), nitrile oxide (CNO), diazomethane (NNC), azine (NNN), and nitrous oxide (NNO) in the gas phase were examined using the density functional theory and CCSD(T) calculations. All of the structures, including the precursor complexes;and the transition structures, were completely optimized at the B3LYP/6-31G* level with single-point energies evaluated at CCSD(T)/6-311G**. The theoretical results suggest that the activation energies for the DC reactions of nitrile-type molecules (CNC, CNN, and CNO) are small (5.1-11 kcal/mol) and these reactions are very exothermic (-77 to -46 kcal/mol). In contrast, the DC reactions of NNC, NNN, and NNO are less exothermic (-39 to -6.0 kcal/mol) and have larger activation barriers (13-29 kcal/mol). Moreover, this work shows that the configuration mixing (CM) model based on Press and Shaik's theory can successfully predict the relative ordering of the activation energy and reaction enthalpies of DC reactions; Combining our theoretical calculations and the CM model, the following conclusion emerges: a 16-electron 1,3-dipole reactant with more electropositive substituents at the terminal positions will possess a smaller singlet-triplet splitting. This will facilitate cycloaddition with the dipolarophile and will result in a larger exothermicity.
Density functional study of the relative reactivity in the concerted 1,3-dipolar cycloaddition of nitrile ylide to disubstituted ethylenes
(2001-07-05)
Liao, HY
;
Su, MD
;
Chung, WS
;
Chu, SY
;
應用化學系
Density functional theory was used to perform a theoretical evaluation of (E)-1,2-disubstituted ethylenes as dipolarophiles for the 1,3-dipolar cycloaddition reaction. The reactivities of electron-withdrawing and -donating substituted ethylenes were examined by estimating their activation energies. The calculated activation energies predicted that the most reactive species is (E)-1,2-C2H2(NO)(2), whereas the least reactive is (E)-2-butene. Namely, it was demonstrated that 16-electron 1,3-dipole reactants with more electropositive substituents in terminal positions and ethylenes that possess more strongly electron-withdrawing substituents facilitate 1,3-dipolar cycloaddition reactions. All of the theoretical results can be rationalized using the configuration mixing model. (C) 2001 John Wiley & Sons, Inc.
Tuning of PID controllers based on gain and phase margin specifications using fuzzy neural network
(1999-01-01)
Chu, SY
;
Teng, CC
;
電控工程研究所
;
Institute of Electrical and Control Engineering
We propose a new PID tuning method using fuzzy neural networks for a given gain and phase margin specifications (FNGP). We use fuzzy neural networks to determine the PID controller parameters. Because the definitions of gain and phase margin equations are complex, an analytical tuning method for achieving specified gain and phase margins is not available yet. In this paper, a fuzzy neural modeling method is first proposed to identify the relationship between the gain-phase margin specifications and the PID controller parameters. Then, the FNGP is used to automatically tune the PID controllers parameter for different gain and phase margin specifications so that neither numerical methods nor graphical methods need be used Simulation results show that the FNGP can achieve the specified Values much more efficiently than other methods. (C) 1999 Elsevier Science B.V. All rights reserved.
Tuning of PID controllers based on gain and phase margin specifications using fuzzy neural network
(1999-01-01)
Chu, SY
;
Teng, CC
;
電控工程研究所
;
Institute of Electrical and Control Engineering
We propose a new PID tuning method using fuzzy neural networks for a given gain and phase margin specifications (FNGP). We use fuzzy neural networks to determine the PID controller parameters. Because the definitions of gain and phase margin equations are complex, an analytical tuning method for achieving specified gain and phase margins is not available yet. In this paper, a fuzzy neural modeling method is first proposed to identify the relationship between the gain-phase margin specifications and the PID controller parameters. Then, the FNGP is used to automatically tune the PID controllers parameter for different gain and phase margin specifications so that neither numerical methods nor graphical methods need be used Simulation results show that the FNGP can achieve the specified Values much more efficiently than other methods. (C) 1999 Elsevier Science B.V. All rights reserved.