Advances in Neural Networks – ISNN 2015: 12th International by Xiaolin Hu, Yousheng Xia, Yunong Zhang, Dongbin Zhao

By Xiaolin Hu, Yousheng Xia, Yunong Zhang, Dongbin Zhao

The quantity LNCS 9377 constitutes the refereed court cases of the twelfth overseas Symposium on Neural Networks, ISNN 2015, held in jeju, South Korea on October 2015. The fifty five revised complete papers awarded have been rigorously reviewed and chosen from ninety seven submissions. those papers hide many issues of neural network-related examine together with clever keep an eye on, neurodynamic research, memristive neurodynamics, laptop imaginative and prescient, sign processing, desktop studying, and optimization.

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Extra resources for Advances in Neural Networks – ISNN 2015: 12th International Symposium on Neural Networks, ISNN 2015, Jeju, South Korea, October 15–18, 2015, Proceedings

Example text

Is defined as ∞ J(x0 , u0 ) = U (xk , uk ), (2) k=0 where U (xk , uk ) > 0, for xk , uk = 0, is the utility function. The goal of this paper is to find an optimal control scheme which stabilizes the system (1) and simultaneously minimizes the performance index function (2). For convenience of analysis, results of this paper are based on the following assumptions. Assumption 1. System (1) is controllable and the function F (xk , uk ) is Lipschitz continuous for xk , uk . Assumption 2. , F (0, 0) = 0.

Diao et al. 5 100 3 (a) The output voltage responses. 5 -1500 0 3 (c) NN estimation of δdc . 5 3 (d) NN estimation of δd . 05 Time/s (b) The supply voltage and input current of phase-A. 5 Time/s (e) NN estimation of δq . (f) The derivatives of the virtual control law. Fig. 3. The simulation results. can approximate the uncertainties quickly and accurately. Fig. 3(f) shows the derivatives of the virtual control law obtained by the LTD and the first-order filter. It can be noticed that the peaking phenomenon of the filter is suppressed by using the LTD, which can ensure the system stability during the initial phase.

IEEE Transactions on Power Electronics 26(5), 1559–1567 (2011) 4. : Robust model predictive current control of three-phase voltage source PWM rectifier with online disturbance observation. IEEE Transactions on Industrial Informatics 8(3), 459–471 (2012) 5. : Feed-forward transient current control for low-voltage ride-through enhancement of DFIG wind turbines. IEEE Transactions on Energy Conversion 25(3), 836–843 (2010) 6. : Study and control of three-phase PWM rectifier based on dual single-input single-output model.

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