This paper proposes a novel consensus dynamics based on the multi-hop communication for fixed and undirected graphs. In the proposed method, each agent updates its state with auxiliary variables which are computed by its multi-hop neighbors. We show that the proposed consensus dynamics achieves an average consensus. We also show that the convergence factor depends on the number of hops.
This paper deals with a dynamic pricing using the H∞ control with uncertain behavior in electricity market trading. The dynamic pricing is a decision procedure of an electricity price based on power supply and demand balance in power grids. However, in a future deregulated electricity market, both power consumers and generators determine their own power demand and supply selfishly according to the price information. Moreover, uncertainties are also included in their behavior. For this problem, we propose a novel price decision method using the locational price-updating H∞ controllers. This paper shows a design process of this price-updating H∞ controller to evaluate the following performance to reduce supply-demand imbalances in power grids and the robustness against uncertainties in electricity market participants' behavior, respectively. In addition, this paper also shows the effectiveness of our proposed price decision method using the designed H∞ controller through numerical simulation results.
An accurate mathematical representation of the impact of carbohydrates on postprandial glucose-insulin metabolism in type 1 diabetes (T1D) is essential for the development of model-based diabetes-related technologies. In this study, the physiological representation of a previous model of gut absorption from carbohydrates is enhanced by including a maximum rate of exogenous glucose appearance as observed in clinical studies in the literature. Simulation results for the same four representative carbohydrate-rich foods with varying glycemic index values as in our previous study, in addition to a sugary beverage, show that the postprandial glycemic excursion relates more closely to clinical data of postprandial glycemic excursion in patients with T1D.
This paper deals with a regional demand response method based on dynamic electricity pricing in a multi-period energy market. In the proposed method, first, the power supply and demand in each area are determined considering power flow using the retail and wholesale electricity prices in a day-ahead market. Next, in a real-time market, the proposed method adjusts to power deviations caused by errors in power generation with power demand reduction by consumers and increased power supply from balancing generators. In addition, in order to guarantee the non-deficiency in the real-time market trading, the incentive and penalty price design methods are discussed in this paper. This paper also shows a distributed algorithm for obtaining the optimal values of each market player in both the day-ahead and real-time markets, and finally, numerical simulation results demonstrate the effectiveness of the proposed method.
This paper is concerned with convergence rate analysis of multi-agent positive systems under formation control. Recently, we have shown that very basic multi-agent systems under formation control can be modeled as interconnected positive systems, and desired formation can be achieved by designing interconnection matrices appropriately. In such formation control, the resulting convergence performance (i.e., convergence rate) varies according to the interconnection matrices and this fact motivates us to develop an efficient algorithm for the analysis of the convergence rate. In this paper, assuming that the dynamics of agents are positive and homogeneous, we conceive such an algorithm by problem decomposition. We show that the decomposition to smaller size problems and drastic reduction of computational burden become possible by making full use of the positivity of the agents.