This paper gives some new results on relations between consensus speed and network topology of multiagent systems, which are useful for design of the systems. Especially, relations between consensus speed and number of edges, difference of the degree, and number of closed paths are shown in the paper by computing the second smallest eigenvalues of the Laplacian matrices. We also show concrete examples of network topologies with redundant edges, which can be removed without reducing consensus speed.

In order to comply with NOx emission regulations, SCR (Selective Catalytic Reduction) system in the diesel engine exhaust gas aftertreatment is required to be precisely controlled in the most efficient temperature range. In this paper, we focus on the feature of the SCR system which inherits various heat transfer delays, and derive a design method of optimized predictive servomechanism which attains favorable transient. The efficacy of the proposed method is evaluated based on rigorous engine simulation, and the strengths and limitations are discussed.

Recently digital twins are widely utilized in various manufacturing stage, and various methods are proposed to compensate the error between digital model and real world. This paper discusses the types of errors that occur in the digital model of a robot and their correction methods. We focus on machine learning methods that can be applied to the target robot with a minimal number of measurement points or without the need for a mechanism model. We state that the RBF interpolation method is generally applicable among the interpolation methods that can effectively utilize the high repeatability accuracy of the robot. We also describe the error estimation process using similarity measure such as k-NN and demonstrate through simulation that the number of teaching points can be efficiently reduced by performing teaching correction in order of the teaching points with the maximum estimated error. Additionally, we proposed a use case based on the automotive spot-welding line and demonstrated that applying this method could potentially reduce the manual teaching points by one-third.

The paper describes a function determination method of an agent in a multi-agent system based on a newly proposed cell differentiation model. Challenges in previous studies in multi-agent systems include dealing with agent failures and being highly dependent on wireless communication. Therefore, we tried to solve these challenges by using cell differentiation in early mammalian embryos, because cells in early mammalian embryos recognize their position and differentiate according to their position in highly robust ways. Namely, we aim to apply the mechanism to the autonomous functional determination of a group of agents that should decide their function according to their relative location in the group. For this aim, the paper proposed an Nf2-Amot complex model of the living cell. The Nf2-Amot model was expected to gain more robust differentiation of living cells. The model together with the conventional model proposed by Caluwé applied to the agents expected to distinguish whether they were located inside or outside of the crowd without any wireless communications. The result showed that the proposed method is more robust than that of using the conventional model.