In this paper, we study a cooperative game in the cooperative communication network, where each relay makes decisions autonomously and aims to achieve the same optimization objective of maximizing energy efficiency. We consider the non-ideal situation where instantaneous channel state information (CSI) is difficult to obtain and only partially observable outdated CSI is available. To solve this game problem, we define a delayed reward-based state-action value function and propose a multi-agent deep Q network learning framework. Then, we prove analytically that utilities obtained by game-theoretic approaches with the instantaneous CSI serve as upper bounds for those of the proposed method. Simulation results reveal that our approach considerably outperforms its potential alternatives and is only about 5.2% away from the optimal solution.
This article develops a large-signal stability analysis for a sampled-data optimization-based secondary controller for distributed energy resources (DERs) in power systems. The induced closed loop combines nonlinear inverter power-flow dynamics, filtered active and reactive power…
Memristors can achieve up to a 1000-times reduction in energy consumption in neuromorphic and in-memory computing, but their integration into power converter control remains incomplete. Existing implementations either convert memristor outputs into digital signals for DSP-based p…
Flexible electronics (FE) platforms rely on analog and mixed-signal (AMS) circuits - biosensors, readout front-ends, and analog-to-digital converters - that dominate both functionality and energy consumption, making on-chip clock generation an essential yet power-critical functio…
We present a traffic-signal control interface in which a shared graph neural network assigns scores to individual traffic movements. Each junction converts these scores into its own variable-sized set of legal signal phases using a deterministic incidence matrix. Directed corrido…
Control barrier functions (CBFs) provide formal safety guarantees for constrained nonlinear systems, but their effectiveness relies on accurate system dynamics. In high-dimensional manipulators subject to unknown disturbances and model uncertainties, fixed safety constraints cons…
An AC and DC hybrid microgrid, which inherits advantages of AC and DC microgrids and discards some disadvantages, is considered to be the most promising power network structure and gradually applied in the community. Usually, the AC subgrid and the DC subgrid are interconnected b…