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Online Supplementary ADP Learning Controller Design and Application to Power System Frequency Control With Large-Scale Wind Energy Integration.

, , , , , and . IEEE Trans. Neural Networks Learn. Syst., 27 (8): 1748-1761 (2016)

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Policy Approximation in Policy Iteration Approximate Dynamic Programming for Discrete-Time Nonlinear Systems., , , and . IEEE Trans. Neural Networks Learn. Syst., 29 (7): 2794-2807 (2018)Online Supplementary ADP Learning Controller Design and Application to Power System Frequency Control With Large-Scale Wind Energy Integration., , , , , and . IEEE Trans. Neural Networks Learn. Syst., 27 (8): 1748-1761 (2016)Error bound analysis of policy iteration based approximate dynamic programming for deterministic discrete-time nonlinear systems., , , , and . IJCNN, page 1-8. IEEE, (2015)Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability., , , , , and . Neurocomputing, (2015)Reactive power control of DFIG wind farm using online supplementary learning controller based on approximate dynamic programming., , , , , and . IJCNN, page 1453-1460. IEEE, (2014)Online adaptation of controller parameters based on approximate dynamic programming., , , and . IJCNN, page 256-262. IEEE, (2014)Non-dominated sorting differential evolution with improved directional convergence and spread for multiobjective optimization., and . GECCO (Companion), page 87-88. ACM, (2014)Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm., , , , and . CoRR, (2017)Incorporating approximate dynamic programming-based parameter tuning into PD-type virtual inertia control of DFIGs., , , and . IJCNN, page 1-8. IEEE, (2013)Policy iteration approximate dynamic programming using Volterra series based actor., , , and . IJCNN, page 249-255. IEEE, (2014)