The multi-microgrids system of the island group is geographically dispersed with different ownership. A control strategy based on distributed model predictive control is proposed to optimize the economic scheduling of multi-microgrids on island group. The strategy is designed based on the dynamic non-cooperative game theory to regulate the trading behavior among microgrids belonging to different owners. The mechanism maximizes the economic benefits of the microgrids under the premise of ensuring the closed-loop stability of the single microgrid system. Only a minimum amount of communication information exchange is needed, which avoids the demands of the central controller and can help the microgrid to protect its privacy of operating information. The proposed strategy can maximize the benefits of power trading and significantly reduce the operating cost of the system while ensuring the balance between supply and demand. Simulation results are presented to prove the fairness and validity of the proposed control strategy.

The electrochemical behavior of iron-doped nickel hydroxide is remarkably consistent across the diverse fabrication protocols employed throughout the literature, which contrasts with variations reported in composition-dependent changes in structure and...

This paper takes a control engineering perspective on the use of rewards to modify the behavior of a person. We consider the particular scenario where a parent is trying to coerce her child to get more physical exercise. The goal is to determine a reward sequence that drives the child's behavior to some desired value. The main novelty of this paper is the introduction of social-norm effects (arising from social pressure due to, say, a teacher) and conformity effects (arising from interactions that the child has with a friend). The social-norm effect, being uni-directional, acts as a disturbance, while the conformity effect, which is bi-directional, creates an extra dynamic feedback loop. We model the psychological state of the child and friend using a combination of psychological theories (the "theory of planned behavior," "cognitive dissonance theory," and "overjustification theory"), and we use classical control tools to design an output-feedback controller that achieves the setpoint tracking objective. Robustness issues are also considered.

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