So far, it has been tried to explain the behavior on experimental subjects in experiments on network formation by a solution concept of the strict Nash equilibrium. In this paper, we consider the correlated equilibrium for network formation which is a solution concept based on stability in terms of expected payoff maximization assuming coordination or implicit agreement between players. To examine its validity, we conduct a laboratory experiment and try to explain the behavior of the experimental subjects. As a result of the experiment, we find that although the explanation by the strict Nash equilibrium is difficult, it is possible to explain by the correlated equilibrium or inequity aversion.
In this paper, an offset compensation method for a continuous-time model predictive control (MPC) is proposed. To achieve offset-free control, additional disturbance states are introduced and the target for MPC is modified based on the estimate of disturbances. The property of steady-state deviation depends on the dimension of the additional disturbance states. An algorithm has already been proposed for discrete-time MPC to achieve zero offset when the model is augmented by disturbance states of the same dimension as tracked variables. We extend this algorithm to continuous-time MPC. A simulation result with the proposed algorithm for a nonlinear tank system is shown.
This paper addresses collision avoidability analysis of a platoon of vehicles under Vehicle-to-Vehicle-to-Infrastructure(V2V2I) communication. We first present a system consisting of vehicular strings and infrastructure in connection. Each vehicle drives automatically connecting others under Vehicle-to-Vehicle(V2V) communication, infrastructure inputs desired inter-vehicular distance to platoon to control safety under Vehicle-to-Infrastructure(V2I) communication. Then we analyze collision avoidability of the vehicle platoon, where we show relationship between communication structure and controllability of safety from infrastructure.