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Energy flow control (EFC) of residential microgrids (RMGs) equipped with renewable generations (RGs) is an essential component for the future smart grid that contributes to enhance renewable energy consumption and reduce cost. Different from most existing papers that devote to offline EFC to against the uncertainties caused by RGs and local load demand in RMGs, this paper focuses on online EFC framework...
Using dictionary atoms to reconstruct input vectors is of great interest in spare representation. However, a key challenge is how to find a proper dictionary. In this paper, we introduce an active dictionary learning (ADL) method which incorporates active learning criteria to select atoms for dictionary construction with the consideration of both classification and reconstruction errors. Specifically,...
In this paper, we study the adaptive-critic-based event-driven robust state feedback stabilization for a class of uncertain nonlinear systems. The novel idea lies in bringing adaptive dynamic programming, a self-learning optimization approach, into nonlinear robust control area under uncertain environment and event-triggering framework. Through theoretical analysis, the nonlinear robust stabilization...
In this paper, we investigate the self-learning optimal guaranteed cost control problem of input-affine continuous-time nonlinear systems possessing dynamical uncertainty. The cost function related to the original uncertain system is discussed sufficiently, with the purpose of developing the optimal guaranteed cost and the corresponding feedback control input. Through theoretical analysis, the optimal...
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